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Wyświetlanie 1-15 z 47
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
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:
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
Artykuł
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
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:
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
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:
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:
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
Artykuł
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
Artykuł
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
Artykuł
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
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
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
Artykuł
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
Artykuł
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