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    Wyświetlanie 1-14 z 14
    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
    Artykuł
    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:
    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
    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:
    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
    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:
    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
    Artykuł
    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
    Artykuł
    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
    Artykuł
    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
    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:
    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
    Artykuł
    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
    Artykuł
    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
    Artykuł
      Wyświetlanie 1-14 z 14

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