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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
Artykuł
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
Artykuł
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
Artykuł
Tytuł:
Multi-objective optimization problem in the OptD-multi method
Autorzy:
Błaszczak-Bąk, Wioleta
Sobieraj-Żłobińska, Anna
Kowalik, Michał
Powiązania:
https://bibliotekanauki.pl/articles/221473.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
reduction
OptD method
optimization
LiDAR
Opis:
New measurement technologies, e.g. Light Detection And Ranging (LiDAR), generate very large datasets. In many cases, it is reasonable to reduce the number of measuring points, but in such a way that the datasets after reduction satisfy specific optimization criteria. For this purpose the Optimum Dataset (OptD) method proposed in [1] and [2] can be applied. The OptD method with the use of several optimization criteria is called OptD-multi and it gives several acceptable solutions. The paper presents methods of selecting one best solution based on the assumptions of two selected numerical optimization methods: the weighted sum method and the ε-constraint method. The research was carried out on two measurement datasets from Airborne Laser Scanning (ALS) and Mobile Laser Scanning (MLS). The analysis have shown that it is possible to use numerical optimization methods (often used in construction) to obtain the LiDAR data. Both methods gave different results, they are determined by initially adopted assumptions and – in relation to early made findings, these results can be used instead of the original dataset for various studies.
Źródło:
Metrology and Measurement Systems; 2019, 26, 2; 253-266
0860-8229
Pojawia się w:
Metrology and Measurement Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
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
Artykuł
Tytuł:
Multi-objective optimization of dielectric layer photonic crystal filter
Autorzy:
Yang, H.
Huang, C.
Meng, S.
Powiązania:
https://bibliotekanauki.pl/articles/174482.pdf
Data publikacji:
2017
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
filter
photonic crystal
weighting factors method
response surface methodology
RSM
Opis:
The weighting factors method and the response surface methodology are used to achieve multi-objective optimization of a dielectric layer photonic crystal filter. The size of period and the transmission quantity are considered simultaneously and a multi-objective optimization model of filter is established, which takes the size of period and transmission quantity to be minimized in stop-band as objectives. Global approximate expressions of the objective and the constraint functions are found by response surface methodology. Then the weighting factors method is employed to convert the model into a quadratic programming model and the optimal parameters can be obtained using sequence quadratic programming. Examples provide the optimized results in three different weight coefficients. The effect of the weighting factors on the value of the objective function is also discussed. Results show that the present method is precise and efficient for multi-objective optimization of a dielectric layer photonic crystal filter.
Źródło:
Optica Applicata; 2017, 47, 1; 29-40
0078-5466
1899-7015
Pojawia się w:
Optica Applicata
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Interactive multi-objective optimization for simulated moving bed processes
Autorzy:
Hakanen, J.
Kawajiri, Y.
Miettinen, K.
Biegler, L. T.
Powiązania:
https://bibliotekanauki.pl/articles/970406.pdf
Data publikacji:
2007
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
multiobjective optimization
interactive methods
Nimbus
interior point optimization
IPOPT
simulated moving bed processes
Opis:
In this paper, efficient optimization techniques are used to solve multi-objective optimization problems arising from Simulated Moving Bed (8MB) processes. SMBs are widely used in many industrial separations of chemical products and they are very challenging from the optimization point of view. With the help of interactive multi-objective optimization, several conflicting objectives can be considered simultaneously without making unnecessary simplifications, as it has been done in previous studies. The optimization techniques used are the interactive NIMBUS™ method and the IPOPT optimizer. To demonstrate the usefulness of these techniques, the results of solving an 8MB optimization problem with four objectives are reported.
Źródło:
Control and Cybernetics; 2007, 36, 2; 283-302
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
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
Artykuł
Tytuł:
The multi - objective optimization of the air transportation fleet structure
Autorzy:
Majka, A.
Powiązania:
https://bibliotekanauki.pl/articles/246578.pdf
Data publikacji:
2013
Wydawca:
Instytut Techniczny Wojsk Lotniczych
Tematy:
air transport
small aircraft
aircraft selection
Opis:
One of the most important factors in the development of modern civilization has become the increase in the significance of mobile and fast means of transportation of people and cargo. Aircraft as the fastest available means in the entire transportation system is the basis in places where the distance in the transportation of people is long and the travel time is short. The present work focuses on passenger transport in the European area using light transport aircraft, which may complement existing air transport and can become a real alternative to those who travel by other means of transport. The system of local transportation will become competitive in relation to other means of transport and will find its place on the market only when it has the highest indicators of efficiency. It can be reached by optimally obtaining passenger aircrafts fleet structure performing transportation tasks and optimizing its functioning. One of the basic problems is the rational selection and use of aircrafts, i.e. the minimization of their quantity while at the same time guarantee complete performance of transporting tasks. The selection of the best method of using the means of transport is connected with a large number of alternative variants, which makes it necessary to use special methods of searching for optimal solutions. The quality of the aircraft fleet should be estimated on the basis of several criteria when taking into account the difference in performing tasks. The way to design a competing aircraft fleet is to choose its characteristics by using advanced methods of multiple objective optimization. This work presents the methodology of the optimal designing of the aircraft fleet using the multitask character of the matter which is based on multiple objective mathematical programming in the concept of the set theory.
Źródło:
Journal of KONES; 2013, 20, 4; 261-268
1231-4005
2354-0133
Pojawia się w:
Journal of KONES
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-Objective Optimization Applied for Planning of Regional European Airlin
Autorzy:
Majka, A.
Powiązania:
https://bibliotekanauki.pl/articles/223868.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
regional air transport
aircraft fleet planning
multiple objective optimization
transport lotniczy
regionalny transport lotniczy
planowanie
optymalizacja
Opis:
Fleet planning is very important elements in the airlines planning process. Fleet planning should answer the question which types of aircraft are required and how many of them are required taking into account the current and future transportation needs. Decision-making in the field of operations has a character of engineering. This process requires consideration of many factors, dependencies and criteria. The article presents the decision problem formulated in the form of a multi-objective mathematical model. This work preliminarily determines the structure of the transportation system which performs carriages on the local routes.
Źródło:
Archives of Transport; 2014, 29, 1; 37-46
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Spacecraft attitude fault tolerant control based on multi-objective optimization
Autorzy:
Moradi, Rouzbeh
Alikhani, Alireza
Fathi Jegarkandi, Mohsen
Powiązania:
https://bibliotekanauki.pl/articles/1839618.pdf
Data publikacji:
2020
Wydawca:
Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:
active fault-tolerant control
spacecraft attitude control
finite time convergence
Pareto-optimal set
Opis:
An active fault tolerant controller is designed for the attitude control of a faulty spacecraft. Feedback linearization and Lyapunov’s direct method are used to solve angular velocity equations and to ensure convergence of the system outputs to reference inputs, respectively. In order to ensure finite time convergence, final time constraints are proposed. Three con- structive objective functions are considered as performance measures and optimized using multi-objective optimization. The results show that the outputs converge to the reference attitudes, even for severe actuator faults/failures.
Źródło:
Journal of Theoretical and Applied Mechanics; 2020, 58, 4; 983-996
1429-2955
Pojawia się w:
Journal of Theoretical and Applied Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
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
Artykuł
Tytuł:
Multi-objective optimization of a medical robot model in transient states
Autorzy:
Ilewicz, G.
Harlecki, A.
Powiązania:
https://bibliotekanauki.pl/articles/196543.pdf
Data publikacji:
2018
Wydawca:
Politechnika Śląska. Wydawnictwo Politechniki Śląskiej
Tematy:
medical robot
dynamics
transient state
optimization
genetic algorithm
finite element method
robot medyczny
dynamika
stan przejściowy
optymalizacja
algorytm genetyczny
metoda elementów skończonych
Opis:
The article describes the method for the multi-objective optimization of a proposed medical robot model, which has been considered in the form of a serial kinematic chain. In the assumed approach, the finite element method was used in order to model the flexibility of manipulator links. To speed up the optimization process, the response surface method was applied, defining the so-called metamodel. In order to uncover the optimal solution, a multi-objective genetic algorithm was used, guaranteeing the optimality of the manipulator model in the Pareto sense. The optimization process was carried out by analysing the selected case of the manipulator’s dynamics. The proposed optimization method allows us to minimize the mass of the manipulator while additionally ensuring the highest possible stiffness of its structure and sufficient strength of its parts. Furthermore, it offers the possibility to eliminate the natural frequency of vibrations of the model close to the resonant frequency.
Źródło:
Zeszyty Naukowe. Transport / Politechnika Śląska; 2018, 99; 79-88
0209-3324
2450-1549
Pojawia się w:
Zeszyty Naukowe. Transport / Politechnika Śląska
Dostawca treści:
Biblioteka Nauki
Artykuł
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
Artykuł
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
Artykuł
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