Temat: Multi-objective Optimization - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Multi-objective conceptual design optimization of a domestic unmanned airship
Autorzy:: Amani, S.
Pourtakdoust, S. H.
Pazooki, F.
Powiązania:: https://bibliotekanauki.pl/articles/949225.pdf
Data publikacji:: 2014
Wydawca:: Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:: airship
multi-objective optimization
Pareto optimality
Opis:: Autonomous airships have gained a high degree of importance over the last decades, both theoretically as well and practically. This is due to their long endurance capability needed for monitoring, observation and communication missions. In this paper, a Multi-Objective Optimization approach (MOO) is followed for conceptual design of an airship taking aerody- namic drag, static stability, performance as well as the production cost that is proportional to the helium mass and the hull surface area, into account. Optimal interaction of the afo- rementioned disciplinary objectives is desirable and focused through the MOO analysis. Standard airship configurations are categorized into three major components that include the main body (hull), stabilizers (elevators and rudders) and gondola. Naturally, component sizing and positioning play an important role in the overall static stability and performance characteristics of the airship. The most important consequence of MOO analysis is that the resulting design not only meets the mission requirement, but will also be volumetrically optimal while having a desirable static and performance characteristics. The results of this paper are partly validated in the design and construction of a domestic unmanned airship indicating a good potential for the proposed approach.
Źródło:: Journal of Theoretical and Applied Mechanics; 2014, 52, 1; 47-60
1429-2955
Pojawia się w:: Journal of Theoretical and Applied Mechanics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Handling insensitivity in multi-physics inverse problems using a complex evolutionary strategy
Rozpoznawanie niewrażliwości w wielokryterialnych problemach odwrotnych przy użyciu złożonej strategii ewolucyjnej
Autorzy:: Sawicki, Jakub
Smołka, Maciej
Łoś, Marcin
Schaefer, Robert
Powiązania:: https://bibliotekanauki.pl/articles/29520322.pdf
Data publikacji:: 2019
Wydawca:: Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:: multi-objective optimization
evolutionary algorithm
inverse problem
Opis:: In this paper we present a complex strategy for the solution of ill posed, in-verse problems formulated as multiobjective global optimization ones. The strategy is capable of identifying the shape of objective insensitivity regions around connected components of Pareto set. The goal is reached in two phases. In the first, global one, the connected components of the Pareto set are localized and separated in course of the multi-deme, hierarchic memetic strategy HMS. In the second, local phase, the random sample uniformly spread over each Pareto component and its close neighborhood is obtained in the specially profiled evolutionary process using multiwinner selection. Finally, each local sample forms a base for the local approximation of a dominance function. Insensitivity region surrounding each connected component of the Pareto set is estimated by a sufficiently low level set of this approximation. Capabilities of the whole procedure was verified using specially-designed two-criterion benchmarks.
Artykuł prezentuje złożoną strategię rozwiązywania źle postawionych problemów odwrotnych sformułowanych jako wielokryterialne zadania optymalizacji globalnej. Opisana strategia umożliwia identyfikację obszarów niewrażliwości funkcji celu wokół spójnych składowych zbioru Pareto. Cel jest osiągany w dwu etapach. W pierwszym z nich — globalnym — składowe spójne zbioru Pareto są lokalizowane i separowane przy pomocy wielopopulacyjnej hierarchicznej strategii memetycznej HMS. W etapie drugim — lokalnym — przy użyciu specjalnie sprofilowanego procesu ewolucyjnego wykorzystującego operator selekcji wyborczej z wieloma zwycięzcami produkowana jest losowa próbka rozłożona jednostajnie na każdej składowej i jej bliskim otoczeniu. Finalnie każda lokalna próbka jest użyta jako baza do zbudowania lokalnej aproksymacji funkcji dominacji. Zbiory poziomicowe tej aproksymacji dla odpowiednio niskich poziomów stanowią przybliżenie zbiorów niewrażliwości wokół składowych spójnych. Możliwości strategii zostały zweryfikowane przy użyciu specjalnie zaprojektowanych dwukryterialnych funkcji testowych.
Źródło:: Computer Methods in Materials Science; 2019, 19, 1; 2-11
2720-4081
2720-3948
Pojawia się w:: Computer Methods in Materials Science
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: The scalarization approach for multi-objective optimization of network resource allocation in distributed systems
Autorzy:: Wesołowski, Z.
Powiązania:: https://bibliotekanauki.pl/articles/92817.pdf
Data publikacji:: 2016
Wydawca:: Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:: distributed system
resource allocation
multi-objective optimization
Opis:: The paper presents a multi-objective optimization framework to the network resource allocation problem, where the aim is to maximize the bitrates of data generated by all agents executed in a distributed system environment. In the proposed approach, the utility functions of agents may have different forms, which allows a more realistic modeling of phenomena occurring in computer networks. A scalarizing approach has been applied to solve the optimization problem.
Źródło:: Studia Informatica : systems and information technology; 2016, 1-2(20); 39-52
1731-2264
Pojawia się w:: Studia Informatica : systems and information technology
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Tuning of a Fuzzy System for Controlling Searching Process In Multi Objective Scheduling Immune Algorithm
Autorzy:: Wosik, I.
Skołud, B.
Powiązania:: https://bibliotekanauki.pl/articles/971215.pdf
Data publikacji:: 2009
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: Immune Algorithm
multi objective optimization
fuzzy system
Opis:: In the paper the Multi Objective Immune Algorithm (MOIA) for an open job shop scheduling problem (OJSP) is proposed. The OJSP belongs to most both time consuming and most complicated problems in scope of searching space. In the paper schedules are evaluated by using three criteria: makespan, flowtime and total tardiness. MOIA proposes a schedule, which is best one, selected from a set of achieved solutions. An affinity threshold is a parameter that controls equilibrium between searching space and solutions diversity in MOIA. The affinity threshold is defined by using fuzzy logic system. In the paper fuzzy system is tuned by selecting shape, size of fuzzy sets, and fuzzy decisions of an affinity threshold. If the fuzzy system is used then neither the knowledge about the affinity threshold nor influence over searching processes is not required from a decision-maker. The application of the fuzzy system makes the process of decision-making user friendly. In the paper efficiency of MOIA before and after the fuzzy system tuning is compared and computational results are presented.
Źródło:: Journal of Machine Engineering; 2009, 9, 1; 130-143
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Single spiking neuron multi-objective optimization for pattern classification
Autorzy:: Juarez-Santini, Carlos
Ornelas-Rodriguez, Manuel
Soria-Alcaraz, Jorge Alberto
Rojas-Domínguez, Alfonso
Puga-Soberanes, Hector J.
Espinal, Andrés
Rostro-Gonzalez, Horacio
Powiązania:: https://bibliotekanauki.pl/articles/385022.pdf
Data publikacji:: 2020
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: multi-objective optimization
spiking neuron
pattern classification
Opis:: As neuron models become more plausible, fewer computing units may be required to solve some problems; such as static pattern classification. Herein, this problem is solved by using a single spiking neuron with rate coding scheme. The spiking neuron is trained by a variant of Multi-objective Particle Swarm Optimization algorithm known as OMOPSO. There were carried out two kind of experiments: the first one deals with neuron trained by maximizing the inter distance of mean firing rates among classes and minimizing standard deviation of the intra firing rate of each class; the second one deals with dimension reduction of input vector besides of neuron training. The results of two kind of experiments are statistically analyzed and compared again a Mono-objective optimization version which uses a fitness function as a weighted sum of objectives.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2020, 14, 1; 73-80
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: New solutions to a multi-objective benchmark problem of induction heating: an application of computational biogeography and evolutionary algorithms
Autorzy:: Di Barba, P.
Dughiero, F.
Forzan, M.
Mognaschi, M. E.
Sieni, E.
Powiązania:: https://bibliotekanauki.pl/articles/140925.pdf
Data publikacji:: 2018
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: induction heating
multi-physics analysis
multi-objective optimization
benchmark
Opis:: In induction heating the design of the inductor implies the solution of coupled electromagnetic and thermal fields, along with the use of optimal design procedures to identify the best possible device or process. The benchmark model proposed, a graphite disk heated by means of induction, is optimized using different optimization algorithms. The design aim requires to achieve a prescribed and uniform temperature distribution in the workpiece maximizing the system efficiency.
Źródło:: Archives of Electrical Engineering; 2018, 67, 1; 139-149
1427-4221
2300-2506
Pojawia się w:: Archives of Electrical Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 7.

Tytuł:: A Survey on multi-objective based parameter optimization for deep learning
Autorzy:: Chakraborty, Mrittika
Pal, Wreetbhas
Bandyopadhyay, Sanghamitra
Maulik, Ujjwal
Powiązania:: https://bibliotekanauki.pl/articles/27312917.pdf
Data publikacji:: 2023
Wydawca:: Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:: deep learning
multi-objective optimization
parameter optimization
neural networks
Opis:: Deep learning models form one of the most powerful machine learning models for the extraction of important features. Most of the designs of deep neural models, i.e., the initialization of parameters, are still manually tuned. Hence, obtaining a model with high performance is exceedingly time-consuming and occasionally impossible. Optimizing the parameters of the deep networks, therefore, requires improved optimization algorithms with high convergence rates. The single objective-based optimization methods generally used are mostly time-consuming and do not guarantee optimum performance in all cases. Mathematical optimization problems containing multiple objective functions that must be optimized simultaneously fall under the category of multi-objective optimization sometimes referred to as Pareto optimization. Multi-objective optimization problems form one of the alternatives yet useful options for parameter optimization. However, this domain is a bit less explored. In this survey, we focus on exploring the effectiveness of multi-objective optimization strategies for parameter optimization in conjunction with deep neural networks. The case studies used in this study focus on how the two methods are combined to provide valuable insights into the generation of predictions and analysis in multiple applications.
Źródło:: Computer Science; 2023, 24 (3); 327--359
1508-2806
2300-7036
Pojawia się w:: Computer Science
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 8.

Tytuł:: Information management in passenger traffic supporting system design as a multi-criteria discrete optimization task
Autorzy:: Galuszka, A.
Krystek, J.
Swierniak, A.
Lungoci, C.
Grzejszczak, T.
Powiązania:: https://bibliotekanauki.pl/articles/229171.pdf
Data publikacji:: 2017
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: multi objective optimization
discrete static optimization
Pareto solutions
integrated systems
Opis:: This paper presents a concept of an Integrated System of Supporting Information Management in Passenger Traffic (ISSIMPT). The novelty of the system is an integration of six modules: video monitoring, counting passenger flows, dynamic information for passengers, the central processing unit, surveillance center and vehicle diagnostics into one coherent solution. Basing on expert evaluations, we propose to present configuration design problem of the system as a multi-objectives discrete static optimization problem. Then, hybrid method joining properties of weighted sum and ε-constraint methods is applied to solve the problem. Solution selections based on hybrid method, using set of exemplary cases, are shown.
Źródło:: Archives of Control Sciences; 2017, 27, 2; 229-238
1230-2384
Pojawia się w:: Archives of Control Sciences
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 9.

Tytuł:: Load Balancing Based on Optimization Algorithms: An Overview
Autorzy:: Mbarek, Fatma
Mosorov, Volodymyr
Powiązania:: https://bibliotekanauki.pl/articles/308122.pdf
Data publikacji:: 2019
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: ant colony optimization
honey bee
load balancing
multi-objective optimization
Opis:: Combinatorial optimization challenges are rooted in real-life problems, continuous optimization problems, discrete optimization problems and other signiﬁcant problems in telecommunications which include, for example, routing, design of communication networks and load balancing. Load balancing applies to distributed systems and is used for managing web clusters. It allows to forward the load between web servers, using several scheduling algorithms. The main motivation for the study is the fact that combinatorial optimization problems can be solved by applying optimization algorithms. These algorithms include ant colony optimization (ACO), honey bee (HB) and multi-objective optimization (MOO). ACO and HB algorithms are inspired by the foraging behavior of ants and bees which use the process to locate and gather food. However, these two algorithms have been suggested to handle optimization problems with a single-objective. In this context, ACO and HB have to be adjusted to multiobjective optimization problems. This paper provides a summary of the surveyed optimization algorithms and discusses the adaptations of these three algorithms. This is pursued by a detailed analysis and a comparison of three major scheduling techniques mentioned above, as well as three other, new algorithms (resulting from the combination of the aforementioned techniques) used to eﬃciently handle load balancing issues.
Źródło:: Journal of Telecommunications and Information Technology; 2019, 4; 3-12
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

Tytuł:: Fuzzy multi-objective supplier selection problem in a supply chain
Autorzy:: Kamal, Murshid
Gupta, Srikant
Raina, Ather Aziz
Powiązania:: https://bibliotekanauki.pl/articles/1177774.pdf
Data publikacji:: 2018
Wydawca:: Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Tematy:: Fuzzy Goal Programming
Multi-objective Optimization
Supplier Selection Problem
Opis:: The decision making of supplier selection and their allocation is one of the main concerns in supply chain management. In this paper, an attempt has been made to obtain an optimal allocation for supplier based on minimizing the net cost, minimizing the net rejections, and minimizing the net late deliveries subject to realistic constraints regarding buyer’s demand, vendors’ capacity, vendors’ quota flexibility, purchase value of items, budget allocation to individual vendor, etc. We convert the problem into single objective fuzzy goal programming problem by using weighted root power mean the method of aggregation with linear, exponential and hyperbolic membership functions. The comparison has been made by assigning different weights to the objective functions. A numerical illustration is provided for the verification of applicability of the approach.
Źródło:: World Scientific News; 2018, 100; 165-183
2392-2192
Pojawia się w:: World Scientific News
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 11.

Tytuł:: Multi-objective heuristic feature selection for speech-based multilingual emotion recognition
Autorzy:: Brester, C.
Semenkin, E.
Sidorov, M.
Powiązania:: https://bibliotekanauki.pl/articles/91588.pdf
Data publikacji:: 2016
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: multi-objective optimization
feature selection
speech-based emotion recognition
Opis:: If conventional feature selection methods do not show sufficient effectiveness, alternative algorithmic schemes might be used. In this paper we propose an evolutionary feature selection technique based on the two-criterion optimization model. To diminish the drawbacks of genetic algorithms, which are applied as optimizers, we design a parallel multicriteria heuristic procedure based on an island model. The performance of the proposed approach was investigated on the Speech-based Emotion Recognition Problem, which reflects one of the most essential points in the sphere of human-machine communications. A number of multilingual corpora (German, English and Japanese) were involved in the experiments. According to the results obtained, a high level of emotion recognition was achieved (up to a 12.97% relative improvement compared with the best F-score value on the full set of attributes).
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2016, 6, 4; 243-253
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 12.

Tytuł:: Necessary optimality conditions for a set valued fractional programming problem in terms of contingent epiderivatives
Autorzy:: Gadhi, A. N.
Idrissi, M. El.
Powiązania:: https://bibliotekanauki.pl/articles/205692.pdf
Data publikacji:: 2018
Wydawca:: Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:: fractional optimization
multi-objective optimization
cone-convex mapping
optimality conditions
subdifferential
Opis:: In this paper, we are concerned with a multi-objective fractional extremal programming problem. Using the concept of subdiﬀerential of cone-convex set valued mappings, introduced by Baier and Jahn (1999), together with the convex separation principle, we give necessary optimality conditions. An example illustrating the usefulness of our results is also provided.
Źródło:: Control and Cybernetics; 2018, 47, 2; 147-156
0324-8569
Pojawia się w:: Control and Cybernetics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 13.

Tytuł:: Multi-objective optimization of vehicle routing problem using evolutionary algorithm with memory
Autorzy:: Podlaski, K.
Wiatrowski, G.
Powiązania:: https://bibliotekanauki.pl/articles/305266.pdf
Data publikacji:: 2017
Wydawca:: Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:: vehicle routing problem
time windows
evolutionary algorithms
multi-objective optimization
Opis:: The idea of a new evolutionary algorithm with memory aspect included is proposed to find multiobjective optimized solution of vehicle routing problem with time windows. This algorithm uses population of agents that individually search for optimal solutions. The agent memory incorporates the process of learning from the experience of each individual agent as well as from the experience of the population. This algorithm uses crossover operation to define agents evolution. In the paper we choose as a base the Best Cost Route Crossover (BCRC) operator. This operator is well suited for VPRTW problems. However it does not treat both of parent symmetrically what is not natural for general evolutionary processes. The part of the paper is devoted to find an extension of the BCRC operator in order to improve inheritance of chromosomes from both of parents. Thus, the proposed evolutionary algorithm is implemented with use of two crossover operators: BCRC and its extended-modified version. We analyze the results obtained from both versions applied to Solomon’s and Gehring & Homberger instances. We conclude that the proposed method with modified version of BCRC operator gives statistically better results than those obtained using original BCRC. It seems that evolutionary algorithm with memory and modification of Best Cost Route Crossover Operator lead to very promising results when compared to the ones presented in the literature.
Źródło:: Computer Science; 2017, 18 (3); 269-286
1508-2806
2300-7036
Pojawia się w:: Computer Science
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 14.

Tytuł:: FACTS location and size for reactive power system compensation through the multi-objective optimization
Autorzy:: Belazzoug, M.
Boudour, M.
Sebaa, K.
Powiązania:: https://bibliotekanauki.pl/articles/229744.pdf
Data publikacji:: 2010
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: reactive dispatch
multi-objective optimization
NSGA-II
SVC
TCSC
FACTS
Opis:: The problem of the FACTS (Flexible Alternative Current Transmission System Devices) location and size for reactive power system compensation through the multi-objective optimization is presented in this paper. A new technique is proposed for the optimal setting, dimension and design of two kinds of FACTS namely: Static Volt Ampere reactive (VAR) Compensator (SVC) and Thyristor Controlled Series Compensator (TCSC) handling the minimization of transmission losses in electrical network. Using the proposed scheme, the type, the location and the rating of FACTS devices are optimized simultaneously. The problem to solve is multi criteria under constraints related to the load flow equations, the voltages, the transformer turn ratios, the active and reactive productions and the compensation devices. Its solution requires the the advanced algorithms to be applied. Thus, we propose an approach based on the evolutionary algorithms (EA) to solve multi-criterion problem. It is similar to the NSGA-II method (Ellitist Non Dominated Sorting Genetic Algorithm). The Pareto front is obtained for continuous, discrete and multiple of five MVArs (Mega Volt Ampere reactive) of compensator devices for the IEEE 57-bus test system (IEEE bus test is a standard network).
Źródło:: Archives of Control Sciences; 2010, 20, 4; 473-489
1230-2384
Pojawia się w:: Archives of Control Sciences
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 15.

Tytuł:: Bi-objective routing in a dynamic network: An application to maritime logistics
Autorzy:: Maskooki, Alaleh
Nikulin, Yury
Powiązania:: https://bibliotekanauki.pl/articles/2050033.pdf
Data publikacji:: 2020
Wydawca:: Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:: travelling salesman
time dependent network
multi-objective optimization
integer programming
Opis:: A bi-objectiveMILP model for optimal routing in a dynamic network with moving targets (nodes) is developed, where all targets are not necessarily visited. Hence, our problem extends the moving target travelling salesman problem. The two objectives aim at finding the sequence of targets visited in a given time horizon by minimizing the total travel distance and maximizing the number of targets visited. Due to a huge number of binary variables, such a problem often becomes intractable in the real life cases. To reduce the computational burden, we introduce a measure of traffic density, based on which we propose a time horizon splitting heuristics. In a real-world case study of greenhouse gas emissions control, using Automatic Identification System data related to the locations of ships navigating in the Gulf of Finland, we evaluate the performance of the proposed method. Different splitting scenarios are analysed numerically. Even in the cases of a moderate scale, the results show that near-efficient values for the two objectives can be obtained by our splitting approach with a drastic decrease in computational time compared to the exact MILP method. A linear value function is introduced to compare the Pareto solutions obtained by different splitting scenarios. Given our results, we expect that the present study is valuable in logistic applications, specifically maritime management services and autonomous navigation.
Źródło:: Control and Cybernetics; 2020, 49, 2; 211--232
0324-8569
Pojawia się w:: Control and Cybernetics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 16.

Tytuł:: Evolutionary multi–objective weather routing of sailboats
Autorzy:: Sobecka, Ewa
Szłapczyński, Rafał
Życzkowski, Marcin
Powiązania:: https://bibliotekanauki.pl/articles/1585076.pdf
Data publikacji:: 2020
Wydawca:: Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:: sailing vessels
weather routing
evolutionary multi-objective optimization
weather forecasts
navigation
Opis:: The paper presents a multi-objective method, which optimises the route of a sailboat. The presented method makes use of an evolutionary multi-objective (EMO) algorithm, which performs the optimisation according to three objective functions: total passage time, a sum of all course alterations made during the voyage and the average angle of heel. The last two of the objective functions reflect the navigator’s and passenger’s comfort, which may decrease with multiple turns or when experiencing an excessive heel angle for a long time. The optimisation process takes into account static bathymetry-related constraints as well as dynamic constraints related to the sailboat’s safety in changing wind and wave conditions. The method makes use of all of the above and finally returns an approximated Pareto set containing non-dominated solutions to the optimisation problem. The developed method has been implemented as a simulation application. The paper includes selected simulation results followed by their discussion.
Źródło:: Polish Maritime Research; 2020, 3; 130-139
1233-2585
Pojawia się w:: Polish Maritime Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 17.

Tytuł:: Multi-objective optimization of high speed vehicle-passenger catamaran by genetic algorithm. Part II. Computational simulations
Autorzy:: Sekulski, Z.
Powiązania:: https://bibliotekanauki.pl/articles/260598.pdf
Data publikacji:: 2011
Wydawca:: Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:: ship structure
multi-objective optimization
evolutionary algorithm
genetic algorithm
Pareto domination
Opis:: Real ship structural design problems are usually characterized by presence of many conflicting objectives. Simultaneously, a complete definition of the optimum structural design requires a formulation of size-topology-shape-material optimization task unifying the optimization problems of the four areas and giving an effective solution of the problem. So far, a significant progress towards the solution of the problem has not been obtained. An objective of the present paper was to develop an evolutionary algorithm for multiobjective optimization of structural elements of large spatial sections of ships. Selected elements of the multi-criteria optimization theory have been presented in detail. Methods for solution of the multi-criteria optimization problems have been discussed with the focus on the evolutionary optimization algorithms. In the paper an evolutionary algorithm where selection takes place based on the aggregated objective function combined with domination attributes as well as distance to the asymptotic solution, is proposed and applied to solve the problem of optimizing structural elements with respect to their weight and surface area on a high speed vehicle-passenger catamaran structure, with several design variables, such as plate thickness, scantlings of longitudinal stiffeners and transverse frames, and spacing between longitudinal and transversal members, taken into account. Details of the computational models were at the level typical for conceptual design. Scantlings were analyzed by using selected rules of a classification society. The results of numerical experiments with the use of the developed algorithm, are presented. They show that the proposed genetic algorithm can be an efficient tool for multi-objective optimization of ship structures. The paper is published in three parts: Part I: Theoretical background on evolutionary multi-objective optimization, Part II: Computational investigations, and Part III: Analysis of the results.
Źródło:: Polish Maritime Research; 2011, 3; 3-30
1233-2585
Pojawia się w:: Polish Maritime Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 18.

Tytuł:: The airport gate assignment problem – multi-objective optimization versus evolutionary multi-objective optimization
Autorzy:: Kaliszewski, I.
Miroforidis, J.
Stańczak, J.
Powiązania:: https://bibliotekanauki.pl/articles/305661.pdf
Data publikacji:: 2017
Wydawca:: Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:: airport gate assignment problem
Evolutionary Multi-objective Optimization
mixed-integer programming
Opis:: In this paper, we approach the Airport Gate Assignment Problem by Multi-objective Optimization as well as Evolutionary Multi-objective Optimization. We solve a bi-criteria formulation of this problem by the commercial mixed-integer programming solver CPLEX and a dedicated Evolutionary Multi-objective Optimization algorithm. To deal with multiple objectives, we apply a methodology that we developed earlier to capture decision-maker preferences in multi-objective environments. We present the results of numerical tests for these two approaches.
Źródło:: Computer Science; 2017, 18 (1); 41-52
1508-2806
2300-7036
Pojawia się w:: Computer Science
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 19.

Tytuł:: On a multi-objective optimization problem arising from production theory
Autorzy:: Roman, Maria
Wieczorek, Andrzej
Powiązania:: https://bibliotekanauki.pl/articles/1338896.pdf
Data publikacji:: 1999
Wydawca:: Polska Akademia Nauk. Instytut Matematyczny PAN
Tematy:: multi-objective optimization
(weakly) efficient solution
household production
(weak) Pareto optimality
Opis:: The paper presents a natural application of multi-objective programming to household production and consumption theory. A contribution to multi-objective programming theory is also included.
Źródło:: Applicationes Mathematicae; 1998-1999, 25, 4; 411-415
1233-7234
Pojawia się w:: Applicationes Mathematicae
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 20.

Tytuł:: A new multi-objective optimization algorithm based on differential evolution and neighborhood exploring evolution strategy
Autorzy:: Lobato, F. S.
Steffen, Jr, V.
Powiązania:: https://bibliotekanauki.pl/articles/91590.pdf
Data publikacji:: 2011
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: multi-objective optimization
differential evolution
neighborhood exploring
evolution strategy
sorting strategy
Opis:: In this paper a new optimization algorithm based on Differential Evolution, non-dominated sorting strategy and neighborhood exploration strategy for guaranteeing convergence and diversity through the generation of neighborhoods of different sizes to potential candidates in the population is presented. The performance of the algorithm proposed is validated by using standard test functions and metrics commonly adopted in the specialized literature. The sensitivity analysis of some relevant parameters of the algorithm is performed and compared with the classical DE algorithm without the strategy of neighborhood exploration and with other state-of-the-art evolutionary algorithms.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2011, 1, 4; 259-267
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 21.

Tytuł:: Milk runs model with overtime: application to cluster supply chain
Autorzy:: Tomczak, M.
Bucoń, R.
Powiązania:: https://bibliotekanauki.pl/articles/390975.pdf
Data publikacji:: 2015
Wydawca:: Politechnika Lubelska. Wydawnictwo Politechniki Lubelskiej
Tematy:: cluster supply chain
mathematical programming
multi-objective optimization
small and medium enterprises
Opis:: Paper identifies obstacles limiting functioning and development of small and medium construction enterprises. It also includes a description of cluster supply chain (CSC) idea as a suggested solution to some of the problems resulting from the small scale of company activities. One of more important issues of every distribution centre, i.e. portions of deliveries smaller than truck capacity for particular consumers, is also discussed. This problem was formulated for the first time in dairy industry, therefore, it was called milk runs. Moreover, the authors of this paper presented the outcome analysis of survey carried out among construction engineers and managers. This study aimed at determining organizational principles for logistic centre working with CSC framework. The mathematical model depicting milk runs deliveries with overtime consideration, done for many construction sites within a distribution centre is presented hereunder. This model may be potentially used to optimize distribution centres working within cluster supply chain framework.
Źródło:: Budownictwo i Architektura; 2015, 14, 4; 139-147
1899-0665
Pojawia się w:: Budownictwo i Architektura
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 22.

Tytuł:: Shape optimization of the muffler shield with regard to strength properties
Autorzy:: Jarosz, Joachim
Długosz, Adam
Powiązania:: https://bibliotekanauki.pl/articles/38903721.pdf
Data publikacji:: 2023
Wydawca:: Instytut Podstawowych Problemów Techniki PAN
Tematy:: muffler shield
evolutionary algorithms
multi-objective optimization
finite element method
optimal design
Opis:: This paper is devoted to the shape optimization of the muffler shield with regard to strength properties. Three different optimization criteria are defined and numerically implemented concerning the strength properties of the shield, and different variants of optimization tasks are solved using both built-in optimization modules and in-house external algorithms. The effectiveness and efficiency of the optimization methods used are compared and presented.
Źródło:: Engineering Transactions; 2023, 71, 3; 351-366
0867-888X
Pojawia się w:: Engineering Transactions
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 23.

Tytuł:: Multi-Objective Optimization of Motor Vessel Route
Autorzy:: Marie, S.
Courteille, E.
Powiązania:: https://bibliotekanauki.pl/articles/117604.pdf
Data publikacji:: 2009
Wydawca:: Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:: route planning
Optimization of Vessel Route
multi-objective optimization
Motor Vessel
Optimal Route
Multi-Objective Genetic Algorithm (MOGA)
Bézier Curve
MATLAB
Opis:: This paper presents an original method that allows computation of the optimal route of a motor vessel by minimizing its fuel consumption. The proposed method is based on a new and efficient meshing procedure that is used to define a set of possible routes. A consumption prediction tool has been developed in order to estimate the fuel consumption along a given trajectory. The consumption model involves the effects of the meteorological conditions, the shape of the hull and the power train characteristics. Pareto-optimization with a Multi-Objective Genetic Algorithm (MOGA) is taken as a framework for the definition and the solution of the multi-objective optimization problem addressed. The final goal of this study is to provide a decision helping tool giving the route that minimizes the fuel consumption in a limited or optimum time.
Źródło:: TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2009, 3, 2; 133-141
2083-6473
2083-6481
Pojawia się w:: TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 24.

Tytuł:: Multi-objective optimal reactive power dispatch to maximize power system social welfare in the presence of generalized unified power flow controller
Autorzy:: Suresh, C. V.
Sivanguraju, S.
Powiązania:: https://bibliotekanauki.pl/articles/141441.pdf
Data publikacji:: 2015
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: generalized unified power flow controller
optimal reactive power dispatch
social welfare
multi-objective optimization
Opis:: In this paper a novel non-linear optimization problem is formulated to maximize the social welfare in restructured environment with generalized unified power flow controller (GUPFC). This paper presents a methodology to optimally allocate the reactive power by minimizing voltage deviation at load buses and total transmission power losses so as to maximize the social welfare. The conventional active power generation cost function is modified by combining costs of reactive power generated by the generators, shunt capacitors and total power losses to it. The formulated objectives are optimized individually and simultaneously as multi-objective optimization problem, while satisfying equality, in-equality, practical and device operational constraints. A new optimization method, based on two stage initialization and random distribution processes is proposed to test the effectiveness of the proposed approach on IEEE-30 bus system, and the detailed analysis is carried out.
Źródło:: Archives of Electrical Engineering; 2015, 64, 3; 405-426
1427-4221
2300-2506
Pojawia się w:: Archives of Electrical Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 25.

Tytuł:: Design of Pareto-Optimal Radar Receive Filters
Autorzy:: De Maio, A.
Piezzo, M.
Iommelli, S.
Farina, A.
Powiązania:: https://bibliotekanauki.pl/articles/227067.pdf
Data publikacji:: 2011
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: radar receive filter design
mismatched filte
design
multi-objective optimization problem
Pareto-optimal points
Opis:: This paper deals with the design of radar receive filters jointly optimized with respect to sidelobe energy and sidelobe peaks via Pareto-optimal theory. We prove that this criterion is tantamount to jointly minimizing two quadratic forms, so that the design can be analytically formulated in terms of a multi-objective optimization problem. In order to solve it, we resort to the scalarization technique, which reduces the vectorial problem into a scalar one using a Pareto weight defining the relative importance of the two objective functions. At the analysis stage, we assess the performance of the receive filters in correspondence of different values of the Pareto weight highlighting the performance compromises between the Integrated Sidelobe Level (ISL) and the Peak Sidelobe Level (PSL).
Źródło:: International Journal of Electronics and Telecommunications; 2011, 57, 4; 477-481
2300-1933
Pojawia się w:: International Journal of Electronics and Telecommunications
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 26.

Tytuł:: Optymalizacja systemów elektroenergetycznych z zastosowaniem obliczeń ewolucyjnych
Optimization of electrical energetic systems with the use of evolutionary computations
Autorzy:: Gajer, M.
Powiązania:: https://bibliotekanauki.pl/articles/276458.pdf
Data publikacji:: 2013
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: systemy elektroenergetyczne
optymalizacja wielokryterialna
obliczenia ewolucyjne
electrical energetic systems
multi-objective optimization
evolutionary computations
Opis:: Tematyka artykułu dotyczy zagadnień związanych z optymalizacją pracy urządzeń wchodzących w skład systemu elektroenergetycznego. W artykule optymalizacja sposobu pracy urządzeń systemu elektroenergetycznego została potraktowana jako optymalizacja wielokryterialna. Głównymi kryteriami branymi pod uwagę podczas poszukiwania rozwiązania są przede wszystkim koszt produkcji energii elektrycznej w rozpatrywanym horyzoncie czasowym oraz całkowita moc termicznych strat przesyłowych powstających w liniach wysokich napięć. Ponadto moc w systemie elektroenergetycznym powinna być zbilansowana, co stanowi kolejne kryterium oceny jakości uzyskiwanych rozwiązań. W celu rozwiązania rozpatrywanego w artykule zagadnienia optymalizacyjnego zaproponowano wykorzystanie techniki obliczeń ewolucyjnych.
The topic of the paper is about the optimization of the mode of work of electrical energetic systems. This kind of optimization is considered as multi-objective optimization. The main criteria that are taken under account are the amount of fuel burnt in energetic blocks in the time unit and total thermal losses in power transmission lines. In the paper in order to solve such multi-objective optimization problem the computational technique base on the use of evolutionary algorithms was implemented.
Źródło:: Pomiary Automatyka Robotyka; 2013, 17, 2; 345-350
1427-9126
Pojawia się w:: Pomiary Automatyka Robotyka
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 27.

Tytuł:: Multi-objective approach for production line equipment selection
Autorzy:: Chehade, H.
Dolgui, A.
Dugardin, F.
Makdessian, L.
Yalaoui, F.
Powiązania:: https://bibliotekanauki.pl/articles/407262.pdf
Data publikacji:: 2012
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: linia produkcyjna
projektowanie
optymalizacja
production line design
line balancing
equipment selection
multi-objective optimization
Opis:: A novel problem dealing with design of reconfigurable automated machining lines is considered. Such lines are composed of workstations disposed sequentially. Each workstation needs the most suitable equipment. Each available piece of equipment is characterized by its cost, can perform a set of operations and requires skills of a given level for its maintenance. A multiobjective approach is proposed to assign tasks, choose and allocate pieces of equipment to workstations taking into account all the problem parameters and constraints. The techniques developed are based on a genetic algorithm of type NSGA-II. The NSGA-II suggested is also combined with a local search. These two genetic algorithms (with and without local search) are tested for several line examples and for two versions of the considered problem: bi-objective and four-objective cases. The results of numerical tests are reported. What is the most interesting is that the assessment of these algorithms is accomplished by using three measuring criteria: the direct measures of gaps, the measures proposed by Zitzler and Thiele in 1999 and the distances suggested by Riise in 2002.
Źródło:: Management and Production Engineering Review; 2012, 3, 1; 4-17
2080-8208
2082-1344
Pojawia się w:: Management and Production Engineering Review
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 28.

Tytuł:: The MOORA method and its application to privatization in a transition economy
Autorzy:: Brauers, W. K.
Zavadskas, E. K.
Powiązania:: https://bibliotekanauki.pl/articles/969961.pdf
Data publikacji:: 2006
Wydawca:: Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:: multi-objective optimization
alternative measurement
discrete alternatives
ratio analysis
sub-objectives
reference point method
Opis:: A new method is proposed for multi-objective optimization with discrete alternatives: MOORA (Multi-Objective Optimization on the basis of Ratio Analysis). This method refers to a matrix of responses of alternatives to objectives, to which ratios are applied. A well established other method for multi-objective optimization is used for comparison, namely the reference point method. Later on, it is demonstrated that this is the best choice among the different competing methods. In MOORA the set of ratios has the square roots of the sum of squared responses as denominators. These ratios, as dimensionless. seem to be the best choice among different ratios. These dimensionless ratios, situated between zero and one, are added in the case of maximization or subtracted in case of minimization. Finally, all alternatives are ranked, according to the obtained ratios. Eventually, to give more importance to an objective, an objective can be replaced by different sub-objectives or a coefficient of importance can be specified. An example on privatization in a transition economy illustrates the application of the method. If application is situated originally in a "welfare" economy, centered on production, MOORA becomes even more significant in a 'wellbeing economy", where consumer sovereignty is assumed.
Źródło:: Control and Cybernetics; 2006, 35, 2; 445-469
0324-8569
Pojawia się w:: Control and Cybernetics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 29.

Tytuł:: A fuzzy approach to multi-objective mixed integer linear programming model for multi-echelon closed-loop supply chain with multi-product multi-time-period
Autorzy:: Akin Bas, Sema
Ahlatcioglu Ozkok, Beyza
Powiązania:: https://bibliotekanauki.pl/articles/406583.pdf
Data publikacji:: 2020
Wydawca:: Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:: closed-loop supply chain management
multi-objective optimization
fuzzy mixed-integerlinear programming
inventory decision
Opis:: By the green point of view, supply chain management (SCM), which contains supplier and location selection, production, distribution, and inventory decisions, is an important subject being examined in recent years by both practitioners and academicians. In this paper, the closed-loop supply chain (CLSC) network that can be mutually agreed by meeting at the level of common satisfaction of conflicting objectives is designed. We construct a multi-objective mixed-integer linear programming (MOMILP) model that allows decision-makers to more effectively manage firms’ closed-loop green supply chain (SC). An ecological perspective is brought by carrying out the recycling, remanufacturing and destruction to SCM in our proposed model. Maximize the rating of the regions in which they are located, minimize total cost and carbon footprint are considered as the objectives of the model. By constructing our model, the focus of customer satisfaction is met, as well as the production, location of facilities and order allocation are decided, and we also carry out the inventory control of warehouses. In our multi-product multi-component multi-time-period model, the solution is obtained with a fuzzy approach by using the min operator of Zimmermann. To illustrate the model, we provide a practical case study, and an optimal result containing a preferable level of satisfaction to the decision-maker is obtained.
Źródło:: Operations Research and Decisions; 2020, 30, 1; 25-46
2081-8858
2391-6060
Pojawia się w:: Operations Research and Decisions
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 30.

Tytuł:: Multi-Objective Optimization of Traffic Signal Timing Using Non-Dominated Sorting Artificial Bee Colony Algorithm for Unsaturated Intersections
Autorzy:: Zhao, H.
He, R.
Su, J.
Powiązania:: https://bibliotekanauki.pl/articles/223879.pdf
Data publikacji:: 2018
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: unsaturated intersection
multi-objective optimization
signal timing
artificial bee colony algorithm
vehicle delay
vehicle stops
Opis:: Vehicle delay and stops at intersections are considered targets for optimizing signal timing for an isolated intersection to overcome the limitations of the linear combination and single objective optimization method. A multi-objective optimization model of a fixed-time signal control parameter of unsaturated intersections is proposed under the constraint of the saturation level of approach and signal time range. The signal cycle and green time length of each phase were considered decision variables, and a non-dominated sorting artificial bee colony (ABC) algorithm was used to solve the multi-objective optimization model. A typical intersection in Lanzhou City was used for the case study. Experimental results showed that a single-objective optimization method degrades other objectives when the optimized objective reaches an optimal value. Moreover, a reasonable balance of vehicle delay and stops must be achieved to flexibly adjust the signal cycle in a reasonable range. The convergence is better in the non-dominated sorting ABC algorithm than in non-dominated sorting genetic algorithm II, Webster timing, and weighted combination methods. The proposed algorithm can solve the Pareto front of a multi-objective problem, thereby improving the vehicle delay and stops simultaneously.
Źródło:: Archives of Transport; 2018, 46, 2; 85-96
0866-9546
2300-8830
Pojawia się w:: Archives of Transport
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 31.

Tytuł:: Ewolucyjna wielokryterialna optymalizacja obserwatorów detekcyjnych
Evolutionary multi-objective optimization of detection observers
Autorzy:: Kowalczuk, Z.
Białaszewski, T.
Powiązania:: https://bibliotekanauki.pl/articles/328360.pdf
Data publikacji:: 2008
Wydawca:: Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
Tematy:: diagnostyka
obserwatory detekcyjne
optymalizacja wielokryterialna
algorytmy genetyczne
diagnosis
detection observers
multi-objective optimization
genetic algorithms
Opis:: W pracy omawiane są możliwości wykorzystania algorytmów ewolucyjnych, opartych na niszowaniu oraz rodzajnikowaniu genetycznym (przypisywaniu rodzajnika), do poszukiwania optymalnych rozwiązań inżynierskich zadań wielokryterialnej optymalizacji. W tego rodzaju obliczeniach skutecznie wykorzystuje się koncepcję Pareto-optymalności oraz rangowania (przypisywania rangi). Realizowany ranking pozwala na uniknięcie arbitralnego ważenia celów kryterialnych (kosztów lub zysków). Zamiast tego, dokonuje się użytecznej klasyfikacji rozwiązań, która bardziej obiektywnie uwzględnia poszczególne kryteria. Jako przykład ilustrujący skuteczność proponowanego podejścia przedstawia się metodologię konstruowania liniowych obserwatorów stanu wykorzystywanych w układach detekcyjnych. Szczególną implementację tego podejścia stanowi projekt systemu diagnostyki bezzałogowego samolotu oraz układu napędowego jednostki pływającej.
In this paper the concept of evolutionary searching using mechanisms of genetic gendering and niching is used for solving engineering multi-objective optimization tasks. In such types of evolutionary computation (EC) the ideas of Pareto optimality and ranking are effectively utilized. Within the ranking approach we avoid arbitrary weighting of optimisation objectives (costs or gains). Instead, a useful classification of the solutions is performed that takes into account particular objectives more appropriately. In order to illustrate the applicability of the proposed variants of EC, we consider the issue of designing detection observers, which serve as a principal element in procedures of detecting faults, which may occur in exemplarily objects, like an unmanned plane and a ship propulsion system.
Źródło:: Diagnostyka; 2008, 1(45); 35-41
1641-6414
2449-5220
Pojawia się w:: Diagnostyka
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 32.

Tytuł:: Adaptive robust PID sliding control of a liquid level system based on multi-objective genetic algorithm optimization
Autorzy:: Mahmoodabadi, M. J.
Taherkhorsandi, M.
Talebipour, M.
Powiązania:: https://bibliotekanauki.pl/articles/206697.pdf
Data publikacji:: 2017
Wydawca:: Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:: sliding mode control
PID control
adaptive control
genetic algorithm
multi-objective optimization
liquid level system
Opis:: Adaptive robust PID sliding mode control optimized by means of multi-objective genetic algorithm is presented in this paper to control a three-tank liquid level system with external disturbances. While PID constitutes a reliable and stable controller, when compared to sliding mode control (SMC); robustness and tracking performance of SMC are higher than those of the PID control. To use the unique features of both controllers, optimal sliding mode control is executed in terms of a supervisory controller to enhance the performance of optimal adaptive PID control and to provide the necessary control inputs. After the design of the control law, control coeﬃcients of all four involved controllers are optimized by using the multi-objective genetic algorithm so as to minimize errors and the input of the controller. Simulations illustrate that the adaptive robust PID sliding controller based on multi-objective genetic algorithm optimization provides a superior response in comparison to the results obtained separately by PID control, sliding mode control, and adaptive PID control, respectively.
Źródło:: Control and Cybernetics; 2017, 46, 3; 227-246
0324-8569
Pojawia się w:: Control and Cybernetics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 33.

Tytuł:: Minimizing greenhouse gas emissions from ships using a Pareto multi-objective optimization approach
Autorzy:: Domachowski, Zygfryd
Powiązania:: https://bibliotekanauki.pl/articles/1573584.pdf
Data publikacji:: 2021
Wydawca:: Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:: minimizing emissions from ships
Pareto multi-objective optimization
minimizing emissions as preference objective
ship routing optimization
hybrid power to lower emissions
Opis:: To confront climate change, decarbonization strategies must change the global economy. According to statements made as part of the European Green Deal, maritime transport should also become drastically less polluting. As a result, the price of transport must reflect the impact it has on the environment and on health. In such a framework, the purpose of this paper is to suggest a novel method for minimizing emissions from ships, based on so-called Pareto multi-objective optimization. For a given voyage by a ship, the problem is to minimize emissions on the one hand and minimize fuel consumption or passage time on the other. Minimizing emissions is considered as the preferred objective. Therefore, the objective of minimizing fuel consumption or passage time needs to be reformulated as a constraint. Solving such a problem consists of finding most favourable path and speed for the ship and satisfying the optimization criteria. Relatively new systems such as hybrid diesel–electric systems have the potential to offer significant emissions benefits. A hybrid power supply utilizes the maximum efficiency of the direct mechanical drive and the flexibility of a combination of combustion power from the prime mover and stored power from energy storage from an electrical supply, at part load and overload. A new report by the American Bureau of Shipping suggests that maritime transport is likely to meet the International Maritime Organization’s target by 2030, solely by using current technology and operational measures. However, this would not be enough to attain the target of reducing CO2 emissions by 2050 by at least 50% compared to 2008. New technologies and operational methods must be applied.
Źródło:: Polish Maritime Research; 2021, 2; 96-101
1233-2585
Pojawia się w:: Polish Maritime Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 34.

Tytuł:: Multi-objective optimization of high speed vehicle-passenger catamaran by genetic algorithm. Part II. Analysis of the results
Autorzy:: Sekulski, Z.
Powiązania:: https://bibliotekanauki.pl/articles/260079.pdf
Data publikacji:: 2011
Wydawca:: Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:: ship structure
multi-objective optimization
evolutionary algorithm
genetic algorithm
Pareto domination
set of non-dominated solutions
Opis:: Real ship structural design problems are usually characterized by presence of many conflicting objectives. Simultaneously, a complete definition of the optimum structural design requires a formulation of size-topology-shape-material optimization task unifying the optimization problems from the four areas and giving an effective solution of the problem. Any significant progress towards solving the problem has not been obtained so far. An objective of the present paper was to develop an evolutionary algorithm for multiobjective optimization of the structural elements of large spatial sections of ships. Selected elements of the multi-criteria optimization theory have been presented in detail. Methods for solution of the multi-criteria optimization problems have been discussed with the focus on the evolutionary optimization algorithms. In the paper an evolutionary algorithm where selection takes place based on the aggregated objective function combined with domination attributes as well as distance to the asymptotic solution, is proposed and applied to solve the problem of optimizing structural elements with respect to their weight and surface area for a high - speed vehicle-passenger catamaran structure, with taking into account several design variables such as plate thickness, scantlings of longitudinal stiffeners and transverse frames, and spacing between longitudinal and transversal members. Details of the computational models were kept at the level typical for conceptual design stage. Scantlings were analyzed by using the selected classification society rules. The results of numerical experiments with the use of the developed algorithm are presented. They show that the proposed genetic algorithm may be considered an efficient tool for multi-objective optimization of ship structures. The paper has been published in the three parts: Part I: Theoretical background on evolutionary multiobjective optimization, Part II: Computational simulations, and Part III: Analysis of the results.
Źródło:: Polish Maritime Research; 2011, 4; 3-13
1233-2585
Pojawia się w:: Polish Maritime Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 35.

Tytuł:: Multi-Objective Optimization of Squeeze Casting Process using Genetic Algorithm and Particle Swarm Optimization
Autorzy:: Patel, G. C. M.
Krishna, P.
Vundavilli, P. R.
Parappagoudar, M. B.
Powiązania:: https://bibliotekanauki.pl/articles/379601.pdf
Data publikacji:: 2016
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: squeeze casting process
multi-objective optimization
genetic algorithm
squeeze casting
prasowanie stopu
optymalizacja wielokryterialna
algorytm genetyczny
Opis:: The near net shaped manufacturing ability of squeeze casting process requiresto set the process variable combinations at their optimal levels to obtain both aesthetic appearance and internal soundness of the cast parts. The aesthetic and internal soundness of cast parts deal with surface roughness and tensile strength those can readily put the part in service without the requirement of costly secondary manufacturing processes (like polishing, shot blasting, plating, hear treatment etc.). It is difficult to determine the levels of the process variable (that is, pressure duration, squeeze pressure, pouring temperature and die temperature) combinations for extreme values of the responses (that is, surface roughness, yield strength and ultimate tensile strength) due to conflicting requirements. In the present manuscript, three population based search and optimization methods, namely genetic algorithm (GA), particle swarm optimization (PSO) and multi-objective particle swarm optimization based on crowding distance (MOPSO-CD) methods have been used to optimize multiple outputs simultaneously. Further, validation test has been conducted for the optimal casting conditions suggested by GA, PSO and MOPSO-CD. The results showed that PSO outperformed GA with regard to computation time.
Źródło:: Archives of Foundry Engineering; 2016, 16, 3; 172-186
1897-3310
2299-2944
Pojawia się w:: Archives of Foundry Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 36.

Tytuł:: Multi-objective optimization of high speed vehicle-passenger catamaran by genetic algorithm. Part I. Theoretical background on evolutionary multi objective optimization
Autorzy:: Sekulski, Z.
Powiązania:: https://bibliotekanauki.pl/articles/259303.pdf
Data publikacji:: 2011
Wydawca:: Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:: ship structure
multi-objective optimization
evolutionary algorithm
genetic algorithm
Pareto domination
set of non-dominated solutions
Opis:: Real ship structural design problems are usually characterized by presence of many conflicting objectives. Simultaneously, a complete definition of the optimal structural design requires a formulation of size-topology-shape-material optimization task unifying the optimization problems from these four areas and giving an effective solution of this problem. So far, a significant progress towards the solution of this problem has not been obtained. An objective of the present paper was to develop an evolutionary algorithm for multi-objective optimization of the structural elements of the large spatial sections of ships. Selected elements of the multi-criteria optimization theory have been presented in details. Methods for solution of the multi-criteria optimization problems have been discussed with the focus on the evolutionary optimization algorithms. In the paper an evolutionary algorithm where selection takes place based on the aggregated objective function combined with domination attributes as well as distance to the asymptotic solution is proposed and applied to solve the problem of optimizing structural elements with respect to their weight and surface area on a high speed vehicle-passenger catamaran structure with several design variables, such as plate thickness, scantlings of longitudinal stiffeners and transverse frames, and spacing between longitudinals and transversal members. Details of the computational models were at the level typical for conceptual design. Scantlings were analyzed using the selected rules of a classification society. The results of numerical experiments with the use of the developed algorithm are presented. They show that the proposed genetic algorithm can be an efficient multi-objective optimization tool for ship structures optimization. The paper will be published in three parts: Part I: Theoretical background on evolutionary multi-objective optimization, Part II: Computational investigations, and Part III: Analysis of the results.
Źródło:: Polish Maritime Research; 2011, 2; 3-18
1233-2585
Pojawia się w:: Polish Maritime Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 37.

Tytuł:: Computationally Efficient Two-Objective Optimization of Compact Microwave Couplers through Corrected Domain Patching
Autorzy:: Kozieł, S.
Bekasiewicz, A.
Powiązania:: https://bibliotekanauki.pl/articles/221065.pdf
Data publikacji:: 2018
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: computer-aided design
compact circuits
microwave couplers
multi-objective optimization
domain patching
surrogate modelling
response correction
Opis:: Finding an acceptable compromise between various objectives is a necessity in the design of contemporary microwave components and circuits. A primary reason is that most objectives are at least partially conflicting. For compact microwave structures, the design trade-offs are normally related to the circuit size and its electrical performance. In order to obtain comprehensive information about the best possible trade-offs, multi-objective optimization is necessary that leads to identifying a Pareto set. Here, a framework for fast multi-objective design of compact micro-strip couplers is discussed. We use a sequential domain patching (SDP) algorithm for numerically efficient handling of the structure bandwidth and the footprint area. Low cost of the process is ensured by executing SDP at the low-fidelity model level. Due to its bi-objective implementation, SDP cannot control the power split error of the coupler, the value of which may become unacceptably high along the initial Pareto set. Here, we propose a procedure for correction of the S-parameters’ characteristics of Pareto designs. The method exploits gradients of power split and bandwidth estimated using finite differentiation at the patch centres. The gradient data are used to correct the power split ratio while leaving the operational bandwidth of the structure at hand intact. The correction does not affect the computational cost of the design process because perturbations are pre-generated by SDP. The final Pareto set is obtained upon refining the corrected designs to the high-fidelity EM model level. The proposed technique is demonstrated using two compact microstrip rat-race couplers. Experimental validation is also provided.
Źródło:: Metrology and Measurement Systems; 2018, 25, 1; 139-157
0860-8229
Pojawia się w:: Metrology and Measurement Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 38.

Tytuł:: Investigating multi-objective time, cost, and risk problems using the Grey Wolf Optimization algorithm
Autorzy:: Yilmaz, Mehmet
Dede, Tayfun
Grzywiński, Maksym
Powiązania:: https://bibliotekanauki.pl/articles/31342511.pdf
Data publikacji:: 2023
Wydawca:: Politechnika Częstochowska
Tematy:: multi-objective optimization
grey wolf optimization algorithm
time-cost-risk
optymalizacja wielocelowa
algorytm optymalizacji szarego wilka
czas-koszt-ryzyko
Opis:: Safety plays a crucial role in construction projects. Safety risks encompass potential hazards such as work accidents, injuries, and security. Consequently, it is important to effectively manage these risks with equal emphasis on time and cost considerations during the project planning phase. Within the scope of this research, the grid and archive-based Grey Wolf Optimizer (GWO) algorithm was employed to investigate multi-objective time-cost-risk problems. By employing the GWO, multiple Pareto solutions were provided to the decisionmaker, facilitating improved decision-making. It was determined that the GWO algorithm yields better results in time-cost-risk problems compared to the Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms.
Źródło:: Budownictwo o Zoptymalizowanym Potencjale Energetycznym; 2023, 12; 79-86
2299-8535
2544-963X
Pojawia się w:: Budownictwo o Zoptymalizowanym Potencjale Energetycznym
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 39.

Tytuł:: Scaling laws for the FE solutions of induction machines
Autorzy:: Nell, Martin
Lenz, Jonas
Hameyer, Kay
Powiązania:: https://bibliotekanauki.pl/articles/141030.pdf
Data publikacji:: 2019
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: evolutionary strategy
finite element method analysis
induction machine
induction motor
loss calculation
multi-objective optimization
scaling laws
Opis:: In this paper a scaling approach for the solution of 2D FE models of electric machines is proposed. This allows a geometrical and stator and rotor resistance scaling as well as a rewinding of a squirrel cage induction machine enabling an efficient numerical optimization. The 2D FEM solutions of a reference machine are calculated by a model based hybrid numeric induction machine simulation approach. In contrast to already known scaling procedures for synchronous machines the FEM solutions of the induction machine are scaled in the stator-current-rotor-frequency-plane and then transformed to the torque-speed-map. This gives the possibility to use a new time scaling factor that is necessary to keep a constant field distribution. The scaling procedure is validated by the finite element method and used in a numerical optimization process for the sizing of an electric vehicle traction drive considering the gear ratio. The results show that the scaling procedure is very accurate, computational very efficient and suitable for the use in machine design optimization.
Źródło:: Archives of Electrical Engineering; 2019, 68, 3; 677-695
1427-4221
2300-2506
Pojawia się w:: Archives of Electrical Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 40.

Tytuł:: System reliability optimization: A fuzzy multi-objective genetic algorithm approach
Optymalizacja niezawodności systemu: metoda rozmytego algorytmu genetycznego do optymalizacji wielokryterialnej
Autorzy:: Mutingi, M.
Powiązania:: https://bibliotekanauki.pl/articles/300808.pdf
Data publikacji:: 2014
Wydawca:: Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:: system reliability optimization
multi-objective optimization
genetic algorithm
fuzzy optimization
redundancy
optymalizacja niezawodności systemu
optymalizacja wielokryterialna
algorytm genetyczny
optymalizacja rozmyta
nadmiarowość
Opis:: System reliability optimization is often faced with imprecise and conflicting goals such as reducing the cost of the system and improving the reliability of the system. The decision making process becomes fuzzy and multi-objective. In this paper, we formulate the problem as a fuzzy multi-objective nonlinear program. A fuzzy multi-objective genetic algorithm approach (FMGA) is proposed for solving the multi-objective decision problem in order to handle the fuzzy goals and constraints. The approach is able flexible and adaptable, allowing for intermediate solutions, leading to high quality solutions. Thus, the approach incorporates the preferences of the decision maker concerning the cost and reliability goals through the use of fuzzy numbers. The utility of the approach is demonstrated on benchmark problems in the literature. Computational results show that the FMGA approach is promising.
Często spotykanym problemem w optymalizacji niezawodności systemu są niedokładnie określone i sprzeczne cele, takie jak zmniejszenie kosztów systemu przy jednoczesnej poprawie jego niezawodności. Proces podejmowania decyzji staje się wtedy rozmyty i wielokryterialny. W niniejszej pracy, sformułowaliśmy ten problem jako rozmyty wielokryterialny program nieliniowy (FMOOP). Zaproponowaliśmy metodę rozmytego wielokryterialnego algorytmu genetycznego (FMGA), która pozwala rozwiązać wielokryterialny problem decyzyjny z uwzględnieniem rozmytych celów i ograniczeń. Podejście to jest uniwersalne, co pozwala na rozwiązania pośrednie, prowadzące do rozwiązań wysokiej jakości. Metoda uwzględnia preferencje decydenta w zakresie celów związanych z kosztami i niezawodnością poprzez wykorzystanie liczb rozmytych. Użyteczność FMGA wykazano na przykładzie wzorcowych problemów z literatury. Wyniki obliczeń wskazują, że podejście FMGA jest obiecujące.
Źródło:: Eksploatacja i Niezawodność; 2014, 16, 3; 400-406
1507-2711
Pojawia się w:: Eksploatacja i Niezawodność
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 41.

Tytuł:: A New Mathematical Model for Multisession Exams-Building Assignment
Autorzy:: Ergul, Z.
Kamisli Ozturk, Z.
Powiązania:: https://bibliotekanauki.pl/articles/1031701.pdf
Data publikacji:: 2017-09
Wydawca:: Polska Akademia Nauk. Instytut Fizyki PAN
Tematy:: Educational timetabling
Examination-building assignment
Multi objective nonlinear optimization
Mixed Integer Programming
Opis:: The educational timetabling problem has been extensively investigated in timetabling literature. However, the problem of assigning exams to examination buildings has not been studied intensively by researchers. We were inspired by Open and Distance Education System exams of Anadolu University. Anadolu University Open and Distance Education System, which is used by approximately two millions of students and has more than two millions of graduates, is a well-known institution in Turkey. In this study, we propose a multi-objective mathematical model for multisession exam-building assignment problem. Objective functions of this model are to minimize the distance between consecutive session buildings for a given student, to maximize the number of occupants of buildings in every session and to minimize the variety of booklets for building in every session. Mathematical model has been found inadequate because students-examination building assignment in the Anadolu University Open Education system is a large size real life problem. Starting from this point of view, an order-based multi-objective heuristic algorithm is developed to solve this problem. The solutions obtained by the proposed algorithm are compared with the solution obtained by the mathematical modelling and the current state of the existing system.
Źródło:: Acta Physica Polonica A; 2017, 132, 3; 1207-1210
0587-4246
1898-794X
Pojawia się w:: Acta Physica Polonica A
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 42.

Tytuł:: A new method of decision making in multi-objective optimal placement and sizing of distributed generators in the smart grid
Autorzy:: Khoshayand, Hossein Ali
Wattanapongsakorn, Naruemon
Mahdavian, Mehdi
Ganji, Ehsan
Powiązania:: https://bibliotekanauki.pl/articles/2202555.pdf
Data publikacji:: 2023
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: backward-forward load distribution
fuzzy logic
iterative search algorithm
multi-objective optimization
shortest distance from the origin
weighted sum
Opis:: One of the most important aims of the sizing and allocation of distributed generators (DGs) in power systems is to achieve the highest feasible efficiency and performance by using the least number of DGs. Considering the use of two DGs in comparison to a single DG significantly increases the degree of freedom in designing the power system. In this paper, the optimal placement and sizing of two DGs in the standard IEEE 33-bus network have been investigated with three objective functions which are the reduction of network losses, the improvement of voltage profiles, and cost reduction. In this way, by using the backward-forward load distribution, the load distribution is performed on the 33-bus network with the power summation method to obtain the total system losses and the average bus voltage. Then, using the iterative search algorithm and considering problem constraints, placement and sizing are done for two DGs to obtain all the possible answers and next, among these answers three answers are extracted as the best answers through three methods of fuzzy logic, the weighted sum, and the shortest distance from the origin. Also, using the multi-objective non-dominated sorting genetic algorithm II (NSGA-II) and setting the algorithm parameters, thirty-six Pareto fronts are obtained and from each Pareto front, with the help of three methods of fuzzy logic, weighted sum, and the shortest distance from the origin, three answers are extracted as the best answers. Finally, the answer which shows the least difference among the responses of the iterative search algorithm is selected as the best answer. The simulation results verify the performance and efficiency of the proposed method.
Źródło:: Archives of Electrical Engineering; 2023, 72, 1; 253--271
1427-4221
2300-2506
Pojawia się w:: Archives of Electrical Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 43.

Tytuł:: Applying optimization techniques on cold-formed C-channel section under bending
Autorzy:: El-Lafy, Heba F.
Elgendi, Elbadr O.
Morsy, Alaa M.
Powiązania:: https://bibliotekanauki.pl/articles/27312402.pdf
Data publikacji:: 2022
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: kształtownik zimnogięty
optymalizacja
algorytm genetyczny
cold-formed sections
single optimization
multi-objective optimization
genetic algorithms
effective width method
C-channel beams
Opis:: There are no standard dimensions or shapes for cold-formed sections (CFS), making it difficult for a designer to choose the optimal section dimensions in order to obtain the most cost-effective section. A great number of researchers have utilized various optimization strategies in order to obtain the optimal section dimensions. Multi-objective optimization of CFS C-channel beams using a non-dominated sorting genetic algorithm II was performed using a Microsoft Excel macro to determine the optimal cross-section dimensions. The beam was optimized according to its flexural capacity and cross-sectional area. The flexural capacity was computed utilizing the effective width method (EWM) in accordance with the Egyptian code. The constraints were selected so that the optimal dimensions derived from optimization would be production and construction-friendly. A Pareto optimal solution was obtained for 91 sections. The Pareto curve demonstrates that the solution possesses both diversity and convergence in the objective space. The solution demonstrates that there is no optimal solution between 1 and 1.5 millimeters in thickness. The solutions were validated by conducting a comprehensive parametric analysis of the change in section dimensions and the corresponding local buckling capacity. In addition, performing a single-objective optimization based on section flexural capacity at various thicknesses The parametric analysis and single optimization indicate that increasing the dimensions of the elements, excluding the lip depth, will increase the section’s carrying capacity. However, this increase will depend on the coil’s wall thickness. The increase is more rapid in thicker coils than in thinner ones.
Źródło:: International Journal of Applied Mechanics and Engineering; 2022, 27, 4; 52--65
1734-4492
2353-9003
Pojawia się w:: International Journal of Applied Mechanics and Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 44.

Tytuł:: Optymalizacja wielokryterialna na podstawie równań regresji procesu nagniatania wybranych części maszyn rolniczych
Multi-objective optimization of the burnishing process on the basis of regression equations for particular agricultural machinery parts
Autorzy:: Kukiełka, K.
Kukiełka, L.
Patyk, R.
Szczepanik, K.
Powiązania:: https://bibliotekanauki.pl/articles/292012.pdf
Data publikacji:: 2011
Wydawca:: Polskie Towarzystwo Inżynierii Rolniczej
Tematy:: maszyna rolnicza
wytwarzanie
regeneracja
nagniatanie
warstwa wierzchnia
optymalizacja wielokryterialna
agricultural machine
production
regeneration
burnishing
surface layer
multi-objective optimization
Opis:: Praca dotyczy określania optymalnych wartości parametrów technologicznych nagniatania tocznego z elektrokontakowym nagrzewaniem, w procesie wytwarzania lub regeneracji części maszyn rolniczych. Badane zmienne wyjściowe w postaci najważniejszych wskaźników eksploatacyjnych (odporność na zacieranie, współczynnik tarcia ślizgowego i zużycie ścierne liniowe) opisano równaniami regresji od parametrów technologicznych. Równania te zastosowano w optymalizacji wielokryterialnej, przy pomocy napisanych skryptów w programie Matlab, na przykładzie części nowej ze stali C55. Opracowano zbiór rozwiązań dopuszczalnych na płaszczyźnie zmiennych sterowalnych (parametrów technologicznych) ze względu na przyjęte kryteria (wskaźniki eksploatacyjne) i ograniczenia.
This paper concerns determination of the optimal technological parameters of burnishing rolling with electrical current, in the production or regeneration of agricultural machinery parts. Examined dependent variables, as the most important operational indicators (scuffing resistance, sliding friction coefficient and linear abrasive wear) were described by regression equations from technological parameters. These equations were used in multi-objective optimization process with delivered scripts in Matlab program, for example a new part made of steel C55. A set of acceptable solutions was developed on the plane of controllable variables (of technological parameters) on account of accepted criteria (operational indicators) and limitations.
Źródło:: Inżynieria Rolnicza; 2011, R. 15, nr 5, 5; 149-156
1429-7264
Pojawia się w:: Inżynieria Rolnicza
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 45.

Tytuł:: Dedicated system for design, analysis and optimization of AC-DC converters
Autorzy:: Piasecki, S.
Szmurlo, R.
Rabkowski, J.
Jasiński, M.
Powiązania:: https://bibliotekanauki.pl/articles/201404.pdf
Data publikacji:: 2016
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: AC-DC converter
multi-objective optimization
design methodology
distributed generation systems
konwerter AC-DC
optymalizacja wielokryterialna
metodologia projektowania
generacja rozproszona
Opis:: This paper presents an originally-developed system for design and optimization of AC-DC converters dedicated in particular to operation in distributed generation systems. The proposed procedure is based on a multi-objective discrete optimization and expert knowledge of electrical engineering, especially power electronics. The required accuracy of calculations is obtained by using the database with real components, while the parameters applied in calculations are based on parameters provided by the manufacturer. The paper presents the foundations and basic system properties, the design and optimization process, and selected optimization results, obtained with a fully functional prototype of the design and optimization system (DaOS).
Źródło:: Bulletin of the Polish Academy of Sciences. Technical Sciences; 2016, 64, 4; 897-905
0239-7528
Pojawia się w:: Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 46.

Tytuł:: Rodzajnikowy dobór struktury kryteriów w zadaniach wielokryterialnej optymalizacji systemów decyzyjnych
Gender criteria structure selection in multi-objective optimization of decision systems
Autorzy:: Kowalczuk, Z.
Białaszewski, T.
Powiązania:: https://bibliotekanauki.pl/articles/156879.pdf
Data publikacji:: 2011
Wydawca:: Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:: wielokryterialna optymalizacja
algorytmy genetyczne
diagnostyka
obserwatory detekcyjne
odporne układy sterowania
multi-objective optimization
genetic algorithms
diagnostic
detection observers
robust control systems
Opis:: Praca poświęcona jest problemowi doboru kryteriów i ich klasyfikacji na grupy rodzajnikowe (warianty) w zadaniach wielokryterialnej optymalizacji systemów decyzyjnych, które związane są m.in. z projektowaniem systemów diagnostyki oraz układów sterowania. Celem naszego podejścia jest efektywne poszukiwanie rozwiązań w zadaniach optymalizacyjnych wyrażonych za pomocą wielu kryteriów, gdzie projektant spotyka się z zagadnieniem Pareto-optymalności, albo zmuszany jest do stosowania klasycznych metod optymalizacji - zwykle silnie upraszczających postawiony problem polioptymalizacji. W przypadku podejścia populacyjnego prezentowana metoda może w istotny sposób ułatwić projektantowi ostateczną ocenę uzyskanych rozwiązań. Skuteczność rozważanej metodologii ilustrują przykłady konstruowania liniowych obserwatorów stanu.
The paper gives an account of research results concerning a project of creating a fully-autonomous robotic decision-making system able to interact with its environment, and based on a mathematical model of human cognitive-behavioural psychology with some elements of personality psychology included. The basic idea of this paper is focused on the concept of possible errors in an intelligent robot control system. The system is a composed result of constructing an Intelligent Decision-making System (IDS) based on several recently developed ideas concerning an interactive cognitive-behavioural organism (Artificial Intelligence and Soft Computing, 2010), a fundamental model of human psychology and an IDS system (MMAR, 2010; Applied Mathematics and Computer Science, 2011) for controlling autonomous robots. Principal notions of IDS (Data-processing system based on cognitive psychology, along with the locations of possible errors), conceptions of discovery (object) and (long-time) memory are introduced. Then the heart of IDS, a personality (emotional) system which consists of systems of emotions and needs (based on the Maslow's theory/pyramid and a fuzzy model of needs), is presented. Furthermore, the paper shows what kind of errors can appear and what are their locations in IDS. Methods of avoiding these errors are also indicated.
Źródło:: Pomiary Automatyka Kontrola; 2011, R. 57, nr 7, 7; 810-813
0032-4140
Pojawia się w:: Pomiary Automatyka Kontrola
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 47.

Tytuł:: Reactive distillation for multiple-reaction systems: optimisation study using an evolutionary algorithm
Autorzy:: Keller, T.
Dreisewerd, B.
Górak, A.
Powiązania:: https://bibliotekanauki.pl/articles/185082.pdf
Data publikacji:: 2013
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: nonequilibrium-stage model
Pareto front
multi-objective optimization
diethyl
carbonate
ethyl methyl carbonate
model równowagi
optymalizacja wielokryterialna
dietyl
węglan
etylo-węglan metylu
Opis:: Reactive distillation (RD) has already demonstrated its potential to significantly increase reactant conversion and the purity of the target product. Our work focuses on the application of RD to reaction systems that feature more than one main reaction. In such multiple-reaction systems, the application of RD would enhance not only the reactant conversion but also the selectivity of the target product. The potential of RD to improve the product selectivity of multiple reaction systems has not yet been fully exploited because of a shortage of available comprehensive experimental and theoretical studies. In the present article, we want to theoretically identify the full potential of RD technology in multiple-reaction systems by performing a detailed optimisation study. An evolutionary algorithm was applied and the obtained results were compared with those of a conventional stirred tank reactor to quantify the potential of RD to improve the target product selectivity of multiple-reaction systems. The consecutive transesterification of dimethyl carbonate with ethanol to form ethyl methyl carbonate and diethyl carbonate was used as a case study.
Źródło:: Chemical and Process Engineering; 2013, 34, 1; 17-38
0208-6425
2300-1925
Pojawia się w:: Chemical and Process Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 48.

Tytuł:: Recent developments in simulation-driven multi-objective design of antennas
Autorzy:: Koziel, S.
Bekasiewicz, A.
Powiązania:: https://bibliotekanauki.pl/articles/201914.pdf
Data publikacji:: 2015
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: computer-aided design
CAD
antenna design
multi-objective optimization
surrogate models
evolutionary algorithms
projektowanie wspomagane komputerowo
projektowanie anteny
model zastępczy
algorytmy ewolucyjne
Opis:: This paper addresses computationally feasible multi-objective optimization of antenna structures. We review two recent techniques that utilize the multi-objective evolutionary algorithm (MOEA) working with fast antenna replacement models (surrogates) constructed as Kriging interpolation of coarse-discretization electromagnetic (EM) simulation data. The initial set of Pareto-optimal designs is subsequently refined to elevate it to the high-fidelity EM simulation accuracy. In the first method, this is realized point-by-point through appropriate response correction techniques. In the second method, sparsely sampled high-fidelity simulation data is blended into the surrogate model using Co-kriging. Both methods are illustrated using two design examples: an ultra-wideband (UWB) monocone antenna and a planar Yagi-Uda antenna. Advantages and disadvantages of the methods are also discussed.
Źródło:: Bulletin of the Polish Academy of Sciences. Technical Sciences; 2015, 63, 3; 781-789
0239-7528
Pojawia się w:: Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:: Biblioteka Nauki

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Tytuł:: Multi-objective optimization with adjusted PSO method on example of cutting process of hardened 18CrMo4 steel
Optymalizacja wielokryterialna skorygowaną metodą PSO na przykładzie procesu skrawania stali 18CrMo4 w stanie zahartowanym
Autorzy:: Stryczek, R.
Pytlak, B.
Powiązania:: https://bibliotekanauki.pl/articles/1366141.pdf
Data publikacji:: 2014
Wydawca:: Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:: toczenie na twardo
metoda optymalizacji wielocząsteczkowej (PSO)
obliczenia ewolucyjne
optymalizacja wielokryterialna
entropia
hard turning
particle swarm optimization (PSO) method
evolutionary computations
multi-objective optimization
entropy
Opis:: W pracy zaproponowano zmodyfikowaną metodę optymalizacji wielocząsteczkowej (PSO) dla problemów optymalizacji wielokryterialnej z dyskretną przestrzenią decyzyjną. W metodzie PSO zmieniono sposób określania momentu bezwładności, współczynnika uczenia oraz współczynnika społecznego. Dodatkowo wprowadzono elitaryzm oraz innowacyjny mechanizm hamowania cząstek chroniący je przed przekraczaniem dopuszczalnych granic przestrzeni decyzyjnej. Zaproponowane podejście zostało zweryfikowane na szeregu aktualnych funkcjach testowych oraz problemie optymalizacji procesu skrawania stali 18CrMo4 w stanie zahartowanym, gdzie porównano je z wynikami uzyskanymi za pomocą algorytmów genetycznych (GA). Uzyskane wyniki wskazują, że zaproponowane podejście jest względnie szybkie i wysoce konkurencyjne w stosunku do innych metod optymalizacji. Autorzy uzyskali bardzo różnorodne, zbieżne i w pełnym zakresie przebiegi frontu Pareto w przestrzeni kryteriów. W celu oceny jakości wygenerowanego zbioru Pareto dla każdego z prezentowanych przykładów wyznaczono ocenę opartą na pomiarze entropii oraz wskaźnika jakości IGD.
In this paper a Modified Particle Swarm Optimization (PSO) method for multi-objective (MO) problems with a discrete decision space is proposed. In the PSO method the procedure to determine inertia weight, learning factor and social factor is modified. In addition, both an elitism strategy and innovative deceleration mechanism preventing the particles from going beyond the limits of decision space are introduced. The proposed approach has been applied to a series of currently used test functions as well as to optimization problems connected with finish hard turning operation, where the obtained results have been compared with those obtained by means of Genetic Algorithms (GA). The results indicate that the proposed approach is relatively quick, and thus it is highly competitive with other optimization methods. The authors have obtained a very good diversity, convergence and a maximum range of the Pareto front in the criteria space. In order to assess the quality of the generated Pareto set for each of presented examples, a rating has been determined based on the entropy measurement and inverted generational distance (IGD).
Źródło:: Eksploatacja i Niezawodność; 2014, 16, 2; 236-245
1507-2711
Pojawia się w:: Eksploatacja i Niezawodność
Dostawca treści:: Biblioteka Nauki

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Tytuł:: Metoda wspomagania podejmowania decyzji grupowej oparta na optymalizacji wielokryterialnej
A method of collective decision making based on multicriteria optimization
Autorzy:: Łodziński, A.
Powiązania:: https://bibliotekanauki.pl/articles/321050.pdf
Data publikacji:: 2014
Wydawca:: Politechnika Śląska. Wydawnictwo Politechniki Śląskiej
Tematy:: decyzja grupowa
optymalizacja wielokryterialna
rozwiązanie symetrycznie efektywne
funkcja skalaryzująca
podejmowanie decyzji grupowej
multi-objective optimization
symmetric-effective result
scalarizing function
decision support systems
Opis:: W artykule przedstawiono metodę podejmowania decyzji grupowej. Decyzja grupowa jest wtedy, gdy grupa osób o odmiennych preferencjach ma podjąć wspólną decyzję. Proces wyboru decyzji grupowej modeluje się za pomocą zadania optymalizacji wielokryterialnej. Zadanie to rozwiązuje się metodą punktu odniesienia. Jest to technika interaktywna, w której każda z osób z grupy określa swoje wymagania w postaci punktu odniesienia, który wyraża pożądane wartości dla jej funkcji oceny. Na podstawie podanych punktów odniesienia konstruowana jest skalarna funkcja osiągnięcia. Maksymalizacja tej funkcji generuje rozwiązanie zadania wielokryterialnego, które jest prezentowane każdej osobie z grupy do akceptacji lub jako podstawa do modyfikacji punktów odniesienia.
This paper presents a method of collective decision-making. Group decision is when a group of people with different preferences is to take a common decision. The selection process of group decision is modeled using a multi-criteria optimization problem. This object is achieved by the reference point method. This method is an interactive technique in which each person in the group determines its requirements as a reference point, which expresses the desired value for the evaluation function. On the basis of these reference points a scalarizing achievement function is constructed. Maximizing this function generates the solution of a multi-criteria task. This solution is presented to each person in the group to accept or as a basis for modifying the reference points.
Źródło:: Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska; 2014, 68; 209-219
1641-3466
Pojawia się w:: Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska
Dostawca treści:: Biblioteka Nauki

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Tytuł:: Methods of universities investment potential improvement
Autorzy:: Vergun, Mykhailo O.
Powiązania:: https://bibliotekanauki.pl/articles/2157547.pdf
Data publikacji:: 2014
Wydawca:: Instytut Studiów Międzynarodowych i Edukacji Humanum
Tematy:: higher education establishment
social and economic conditions of market economy
investment potential
factors of the development
multi-objective optimization
fixed assets
sources of financing
Opis:: The current article considers the issues of increasing the efficiency of processes of implementation of the investment potential of universities by optimizing sources of financing, taking into account the features of modern social and economic situation in Ukraine.
Źródło:: Społeczeństwo i Edukacja. Międzynarodowe Studia Humanistyczne; 2014, 3(15); 49-54
1898-0171
Pojawia się w:: Społeczeństwo i Edukacja. Międzynarodowe Studia Humanistyczne
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 52.

Tytuł:: Comparison of a Perpetual and PD Inventory Control System with Smith Predictor and Different Shipping Delays Using Bicriterial Optimization and SPEA2
Analiza porównawcza systemu sterowania ciągłego oraz z regulatorem PD i predyktorem Smitha dla różnych opóźnień dostaw z zastosowaniem metod optymalizacji dwukryterialnej i SPEA2
Autorzy:: Chołodowicz, E.
Orłowski, P.
Powiązania:: https://bibliotekanauki.pl/articles/275128.pdf
Data publikacji:: 2016
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: inventory control systems
optimization
perpetual inventory system
multi-objective optimization
SPEA2
PD control
Smith predictor
inventory
systemy zarządzania zapasami
optymalizacja
optymalizacja wielokryterialna
system sterowania
predyktor Smitha
Opis:: Inventory optimization is critical in inventory control systems. The complexity of real-world inventory systems results in a challenging optimization problem, too complicated to solve by conventional mathematical programing methods. The aim of this work is to confront: a perpetual inventory system found in the literature and inventory system with PD control and Smith predictor proposed by the authors. To be precise, the two control systems for inventory management are analyzed with different shipping delays and compared. With regard to complexity of the proposed control system, we use a SPEA2 algorithm to solve optimization task for assumed scenario of the market demand. The objective is to minimize the inventory holding cost while avoiding shortages. A discrete-time, dynamic model of inventory system is assumed for the analysis. In order to compare the results of systems, Pareto fronts and signal responses are generated.
W pracy przyjęto dyskretny, stacjonarny, dynamiczny model systemu magazynowego ze stałym w czasie opóźnieniem dostaw. Głównym celem jest przeprowadzenie analizy porównawczej dwóch systemów automatycznego sterowania zamówieniami: ciągłego systemu sterowania magazynem z adaptacyjnym poziomem zamówienia (ang. Perpetual Inventory System with adaptive order level) oraz systemu sterowania magazynem z regulatorem proporcjonalno-różniczkującym oraz predyktorem Smitha z adaptacyjnym poziomem referencyjnym zapasów dla trzech różnych opóźnień dostaw. Optymalne nastawy układów regulacji zostały dobrane za pomocą algorytmu ewolucyjnego dla problemów optymalizacji wielokryterialnej: SPEA2 (ang. Strength Pareto Evolutionary Approach). W symulacji uwzględniono dwa kryteria minimalizacji: koszt utrzymania zapasów (ang. Holding Cost) oraz koszt niedoboru zapasu (ang. Shortage Cost). Wyniki badań symulacyjnych zaprezentowano za pomocą wykresów oraz tabel w środowisku MATLAB/Simulink.
Źródło:: Pomiary Automatyka Robotyka; 2016, 20, 3; 5-12
1427-9126
Pojawia się w:: Pomiary Automatyka Robotyka
Dostawca treści:: Biblioteka Nauki

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Tytuł:: A novel hybrid cuckoo search algorithm for optimization of a line-start PM synchronous motor
Autorzy:: Knypiński, Łukasz
Powiązania:: https://bibliotekanauki.pl/articles/2204509.pdf
Data publikacji:: 2023
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: hybrid cuckoo search algorithm
heuristic algorithms
multi-objective optimization
permanent magnet synchronous motor
PMSM
algorytm kukułki hybrydowy
algorytm Cuckoo
algorytm heurystyczny
optymalizacja wielocelowa
silnik synchroniczny z magnesem trwałym
Opis:: The paper presents a novel hybrid cuckoo search (CS) algorithm for the optimization of the line-start permanent magnet synchronous motor (LSPMSM). The hybrid optimization algorithm developed is a merger of the heuristic algorithm with the deterministic Hooke–Jeeves method. The hybrid optimization procedure developed was tested on analytical benchmark functions and the results were compared with the classical cuckoo search algorithm, genetic algorithm, particle swarm algorithm and bat algorithm. The optimization script containing a hybrid algorithm was developed in Delphi Tiburón. The results presented show that the modified method is characterized by better accuracy. The optimization procedure developed is related to a mathematical model of the LSPMSM. The multi-objective compromise function was applied as an optimality criterion. Selected results were presented and discussed.
Źródło:: Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 1; art. no. e144586
0239-7528
Pojawia się w:: Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:: Biblioteka Nauki

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Tytuł:: Wybrane zagadnienia wielokryterialnego planowania sieci WLAN
Selected issues of multi-objective WLAN planning
Autorzy:: Pieprzycki, A.
Ludwin, W.
Powiązania:: https://bibliotekanauki.pl/articles/93106.pdf
Data publikacji:: 2018
Wydawca:: Państwowa Wyższa Szkoła Zawodowa w Tarnowie
Tematy:: wielokryterialny algorytm optymalizacji
planowanie
WLAN
optymalizacja nieliniowa
cuckoo search
multi objective swarm optimization
multiobjective cuckoo search
WLAN planning
non–linear optimization
Opis:: Celem artykułu jest zastosowanie wielokryterialnego podejścia do planowania MOO (Multi Objective Optimisation) sieci łączności bezprzewodowej WLAN (Wireless Local Area Network) z wykorzystaniem wybranych rojowych metod optymalizacji. W tym celu, w procesie poszukiwania ekstremów dwóch funkcji kryterialnych, które są wskaźnikiem optymalizacyjnych, zastosowano dwa algorytmy rojowe: kukułki MOCS (Multi Objective Cuckoo Search) oraz optymalizacji rojem cząstek MOPSO (Multi Objective Particle Swarm Optimisation). Wyniki porównano z jednokryterialnym SOO (Single Objective Optimisation) zasięgowym planowaniem sieci bazującym na regularnym rozmieszczeniu punktów testujących TP (test point) z wykorzystaniem rojowego algorytmu kukułki CS (Cuckoo Search).
The aim of the article is to apply a multicriteria approach to MOO (Multi Objective Optimization) planning for WLAN (Wireless Local Area Network) using selected swarm optimization methods. For this purpose, in the process of searching for the extremum of two criterion functions, which are an optimization index, two swarm algorithms were used: MOCS (Multi Objective Cuckoo Search) and MOPSO (Multi Objective Particle Swarm Optimization). The results were compared with the single-criterion SOO (Single Objective Optimization) range-based network planning based on the regular distribution of TP (test point) using the CS Cuckoo Search algorithm.
Źródło:: Science, Technology and Innovation; 2018, 3, 2; 69-78
2544-9125
Pojawia się w:: Science, Technology and Innovation
Dostawca treści:: Biblioteka Nauki

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Tytuł:: Generalized route planning approach for hazardous materials transportation with equity consideration
Autorzy:: Chai, H.
He, R.-C.
Jia, X.-yan
Ma, Ch.-x
Dai, C.-jie
Powiązania:: https://bibliotekanauki.pl/articles/223759.pdf
Data publikacji:: 2018
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: hazardous materials transportation
transportation
route optimization
risk equity
multi-objective optimization
NSGA-II algorithm
genetic algorithm
transport materiałów niebezpiecznych
materiały niebezpieczne
optymalizacja trasy
kapitał własny
optymalizacja wielokryterialna
algorytm NSGA-II
algorytm genetyczny
Opis:: Hazardous materials transportation should consider risk equity and transportation risk and cost. In the hazardous materials transportation process, we consider risk equity as an important condition in optimizing vehicle routing for the long-term transport of hazardous materials between single or multiple origin-destination pairs (O-D) to reduce the distribution difference of hazardous materials transportation risk over populated areas. First, a risk equity evaluation scheme is proposed to reflect the risk difference among the areas. The evaluation scheme uses standard deviation to measure the risk differences among populated areas. Second, a risk distribution equity model is proposed to decrease the risk difference among populated areas by adjusting the path frequency between O-D pairs for hazardous materials transportation. The model is converted into two sub models to facilitate decision-making, and an algorithm is provided for each sub model. Finally, we design a numerical example to verify the accuracy and rationality of the model and algorithm. The numerical example shows that the proposed model is essential and feasible for reducing the complexity and increasing the portability of the transportation process.
Źródło:: Archives of Transport; 2018, 46, 2; 33-46
0866-9546
2300-8830
Pojawia się w:: Archives of Transport
Dostawca treści:: Biblioteka Nauki

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Tytuł:: Handling fuzzy systems’ accuracy-interpretability trade-off by means of multi-objective evolutionary optimization methods – selected problems
Autorzy:: Gorzałczany, M. B.
Rudziński, F.
Powiązania:: https://bibliotekanauki.pl/articles/199824.pdf
Data publikacji:: 2015
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: accuracy and interpretability of fuzzy rule-based systems
multi-objective evolutionary optimization
genetic computations
fuzzy systems
dokładność systemów rozmytych
optymalizacja
obliczenia genetyczne
systemy rozmyte
Opis:: The paper addresses several open problems regarding the automatic design of fuzzy rule-based systems (FRBSs) from data using multi-objective evolutionary optimization algorithms (MOEOAs). In particular, we propose: a) new complexity-related interpretability measure, b) efficient strong-fuzzy-partition implementation for improving semantics-related interpretability, c) special-coding-free implementation of rule base and original genetic operators for its processing, and d) implementation of our ideas in the context of well-known MOEOAs such as SPEA2 and NSGA-II. The experiments demonstrate that our approach is an effective tool for handling FRBSs’ accuracy-interpretability trade-off, i.e, designing FRBSs characterized by various levels of such a trade-off (in particular, for designing highly interpretability-oriented systems of still competitive accuracy).
Źródło:: Bulletin of the Polish Academy of Sciences. Technical Sciences; 2015, 63, 3; 791-798
0239-7528
Pojawia się w:: Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 57.

Tytuł:: Numerical application of the SPEA algorithm to reliability multi-objective optimization
Autorzy:: Guze, S.
Powiązania:: https://bibliotekanauki.pl/articles/2069179.pdf
Data publikacji:: 2015
Wydawca:: Uniwersytet Morski w Gdyni. Polskie Towarzystwo Bezpieczeństwa i Niezawodności
Tematy:: multi-objective
optimization
reliability
0-1 knapsack problem
SPEA
Opis:: The main aim of the paper is the computer-aided multi-objective reliability optimization using the SPEA algorithm. This algorithm and the binary knapsack problem are described. Furthermore, the computer program that solves the knapsack problem with accordance to SPEA algorithm is introduced. Example of the possible application of this program to the multi-objective reliability optimization of exemplary parallel-series system is shown.
Źródło:: Journal of Polish Safety and Reliability Association; 2015, 6, 1; 101--114
2084-5316
Pojawia się w:: Journal of Polish Safety and Reliability Association
Dostawca treści:: Biblioteka Nauki

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Tytuł:: Optimising rig design for sailing yachts with Evolutionary Multi-objective Algorithm
Autorzy:: Pawłusik, Mikołaj
Szłapczyński, Rafał
Karczewski, Artur
Powiązania:: https://bibliotekanauki.pl/articles/1573832.pdf
Data publikacji:: 2020
Wydawca:: Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:: sailing yacht rig optimization
Bermuda sloop
Multi-Objective Evolutionary Algorithms (MOEA)
Multi Criteria Decision Making (MCDM)
Opis:: The paper presents a framework for optimising a sailing yacht rig using Multi-objective Evolutionary Algorithms and for filtering obtained solutions by means of a Multi-criteria Decision Making method. A Bermuda sloop with discontinuous rig is taken under consideration as a model rig configuration. It has been decomposed into its elements and described by a set of control parameters to form a responsive model which can be used for optimisation purposes. Considering the contradictory nature of real optimisation objectives, a multi-objective approach has been chosen to address this issue. Once the optimisation process is over, a Multi-criteria Decision Making method based on a w-dominance relation is applied for filtering out the most interesting solutions from the obtained Pareto set. The proposed method has been implemented, and selected results are provided and discussed.
Źródło:: Polish Maritime Research; 2020, 4; 36-49
1233-2585
Pojawia się w:: Polish Maritime Research
Dostawca treści:: Biblioteka Nauki

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Tytuł:: Multi-objective optimization of PCM-fin structure for staggered Li-ion battery packs
Autorzy:: Qiu, Chenghui
Wu, Chongtian
Yuan, Xiaolu
Wu, Linxu
Yang, Jiaming
Shi, Hong
Powiązania:: https://bibliotekanauki.pl/articles/27311457.pdf
Data publikacji:: 2023
Wydawca:: Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:: staggered arrangement
phase change material
fin
multi-objective optimization
thermal management
entropy weight
TOPSIS method
technique for order of preference by similarity to ideal solution
układ naprzemienny
materiał o przemianie fazowej
materiał zmieniający fazę
płetwa
optymalizacja wielocelowa
optymalizacja wieloobiektowa
zarządzanie ciepłem
entropia wagi
metoda TOPSIS
technika porządkowania preferencji według podobieństwa do idealnego rozwiązania
Opis:: Endurance capability is a key indicator to evaluate the performance of electric vehicles. Improving the energy density of battery packs in a limited space while ensuring the safety of the vehicle is one of the currently used technological solutions. Accordingly, a small space and high energy density battery arrangement scheme is proposed in this paper. The comprehensive performance of two battery packs based on the same volume and different space arrangements is compared. Further, based on the same thermal management system (PCM-fin system), the thermal performance of staggered battery packs with high energy density is numerically simulated with different fin structures, and the optimal fin structure parameters for staggered battery packs at a 3C discharge rate are determined using the entropy weight-TOPSIS method. The result reveals that increasing the contact thickness between the fin and the battery (X) can reduce the maximum temperature, but weaken temperature homogeneity. Moreover, the change of fin width (A) has no significant effect on the heat dissipation performance of the battery pack. Entropy weight-TOPSIS method objectively assigns weights to both maximum temperature (Tmax) and temperature difference (DT) and determines the optimal solution for the cooling system fin parameters. It is found that when X = 0:67 mm, A = 0:6 mm, the staggered battery pack holds the best comprehensive performance.
Źródło:: Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 4; art. no. e145677
0239-7528
Pojawia się w:: Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:: Biblioteka Nauki

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Tytuł:: Multi-objective Channel Decision for Adhoc Cognitive Radio Network
Autorzy:: Awathankar, Rahul V
Rukmini, M S S
Raut, Rajeshree D
Powiązania:: https://bibliotekanauki.pl/articles/226079.pdf
Data publikacji:: 2019
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: cognitive radio networks
ranking and optimization
cooperative network
channel decision
multi objective decision making(MODM)
MOORA method
Opis:: Faithfull detection of non-utilized spectrum hole in available channel is a crucial issue for cognitive radio network. Choosing the best available channel for a secondary user transmission includes settling on decision of accessible choices of free frequency spectrum based on multiple objectives. Thus channel judgment can be demonstrated as several objective decision making (MODM) problem. An ultimate goal of this exploration is to define and execute a technique for multiple objective optimizations of multiple alternative of channel decision in Adhoc cognitive radio network. After a coarse review of an articles related to the multiple objective decision making within a process of channel selection, Multiple Objective Optimization on the basis of the Ratio Analysis (MOORA) technique is taken into consideration. Some important objectives values of non-utilized spectrum collected by a fusion center are proposed as objectives for consideration in the decision of alternatives. MOORA method is applied to a matrix f replies of each channel alternatives to channel objectives which results in set ratios. Among the set of obtained dimensionless ratios, all the channel alternatives are ranked in descending order. In MOORA, channel choices with moderate objectives can top in ranking order, which is hardly conceivable with linearly weighted objectives of the different channel by using different decision making technique.
Źródło:: International Journal of Electronics and Telecommunications; 2019, 65, 2; 253-257
2300-1933
Pojawia się w:: International Journal of Electronics and Telecommunications
Dostawca treści:: Biblioteka Nauki

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Tytuł:: Multi-objective dynamic economic dispatch using Fruit Fly Optimization method
Autorzy:: Arsyad, Haripuddin
Suyuti, Ansar
Said, Sri Mawar
Akil, Yusri Syam
Powiązania:: https://bibliotekanauki.pl/articles/1841297.pdf
Data publikacji:: 2021
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: dynamic economic dispatch
Fruit Fly Optimization method
multi-objective
dynamiczna wysyłka ekonomiczna
Metoda optymalizacji muszki owocowej
wielocelowy
Opis:: An essential task of the interconnected power system is about how to optimize power plants during operation time which is known as economic dispatch. In this study, the Fruit Fly Optimization method is proposed to solve problems of dynamic economic dispatch in an electrical power system. To measure the performance of the method, a simulation was conducted for two different electric systems of the existing Sulselbar 150 kV thermal power plant system in Indonesia with two objective functions, namely fuel costs and active power transmission losses, aswell as the 30-bus IEEE standard system with five objective functions namely fuel costs, transmission losses (active and reactive power), a reactive power reserve margin, and an emission index by considering a power generation limit and ramp rates as the constraints. Under tested cases, the simulation results have shown that the Fruit Fly Optimization method can solve the problems of dynamic economic dispatch better than other existing optimization methods. It is indicated by all values of the objective functions that are lowest for the Fruit Fly Optimization method. Moreover, the obtained computational time is sufficiently fast to get the best solution.
Źródło:: Archives of Electrical Engineering; 2021, 70, 2; 351-366
1427-4221
2300-2506
Pojawia się w:: Archives of Electrical Engineering
Dostawca treści:: Biblioteka Nauki

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Tytuł:: Multicriteria optimization method of LNG distribution
Autorzy:: Chłopińska, E.
Gucma, M.
Powiązania:: https://bibliotekanauki.pl/articles/117110.pdf
Data publikacji:: 2020
Wydawca:: Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:: cargo handling
Liquefied Natural Gas (LNG)
Multicriteria Optimization Method
LNG Distribution
Marine Diesel Oil (MDO)
Heavy Fuel Oil (HFO)
Vector Evaluated Genetic Algorithms (VEGA)
Multi-Objective Genetic Algorithm (MOGA)
Opis:: Liquefied Natural Gas (LNG) is considered as a realistic substation of marine fuel in 21 century. Solution of building new engines or converting diesels into gas fueled propulsion meets the stringent international emission regulations. For HFO (heavy fuel oil) or MDO (marine diesel oil) propelled vessels, operation of bunkering is relatively wide known and simple. Its due to the fact that fuel itself doesn’t require high standards of handling. Where for LNG as a fuel its very demanding process – it evaporates and requires either consuming by bunker vessel or reliquefication. Distribution of such bunker is becoming multidimensional problem with time and space constrains. The objective of the article is to review the methods of optimization using genetic algorithms for a model of LNG distribution. In particular, there will be considered methods of solving problems with many boundry criteria whose objective functions are contradictory. Methods used for solving the majority of problems are can prevent the simultaneous optimization of the examined objectives, e.g. the minimisation of costs or distance covered, or the maximisation of profits or efficiency etc. Here the standard genetic algorithms are suitable for solving multi-criteria problems by using functions producing a diversity of results depending on the adopted approach.
Źródło:: TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2020, 14, 2; 493-497
2083-6473
2083-6481
Pojawia się w:: TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:: Biblioteka Nauki

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