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New trends in optimization in electromagnetics

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PL
Nowe tendencje optymalizacji w elektrodynamice technicznej
Języki publikacji
EN
Abstrakty
EN
This paper reviews recent advances in optimisation of electromagnetic problems. CAD assisted optimal design often necessitates repetitive usage of numerically intensive field computation where cost-effective approaches are required. Modern algorithms increasingly rely on surrogate modelling, kriging-assisted methods, pareto-optimality and design sensitivity.
PL
Nowoczesne metody projektowania oparte na wspomaganiu komputerowym z wykorzystaniem numerycznego oblicznia pól elektromagnetycznych wymagają skutecznych, a przede wszystkim szybkich i efektywnych metod optymalizacyjnych. Ostatnie lata przyniosły eksplozję nowych podejść i algorytmów. Artykuł jest próbą uogólnienia efektów ostatnich badań – w tym również dorobku autora – ze szczególnym uwzględnieniem najnowszych osiągnięć i spodziewanych nowych rozwiązań.
Rocznik
Strony
13--18
Opis fizyczny
Bibliogr. 32 poz., rys., tab., wykr.
Twórcy
autor
Bibliografia
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  • [9]Di Barba P., Nash equilibrium and pareto front for the optimal shape design in electromechanics, In Proceedings of 6th International Conference on Computational Electromagnetics, (2006), 123–124
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  • [13]Canova A., Freschi F., Repetto M., Hybrid method coupling ais and zeroth order deterministic search, COMPEL, 24 (2005), No. 3, 784–795
  • [14]Mullur A. A., Messac A., Metamodeling using extended radial basis functions: a comparitive approach, Engineering with Computers, 21 (2006), 203–217
  • [15]Chen V. C. P., Tsui K-W., Barton R. R., Meckesheimer M., A review on design, modeling and applications of computer experiments, IIE Transactions, 38 (2006), 273–291
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  • [20]Knowles J., ParEGO: A hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems, IEEE Trans. Evol. Comp., 10 (2006), No. 1, 50–66
  • [21]Lebensztajn L., et al, A multi-objective analysis of a special switched reluctance motor, COMPEL, 24 (2005), No. 3, 931–941
  • [22]Emmerich M. T. M., Giannakoglou K. C., Naujoks B., Single- and multiobjective evolutionary optimization assisted by gaussian random field metamodels, IEEE Trans. Evol. Comp., 10 (2006), No. 4, 421–439
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  • [26] Sykulski J. K., Reducing computational effort in field optimisation problems, COMPEL, 23 (2004), No. 1, 159-172
  • [27] Hawe G. I., Sykulski J. K., A hybrid one-then-two stage algorithm for computationally expensive electromagnetic design optimization, COMPEL, 26 (2007), No. 2, 240–250
  • [28] Matlab, High-Performance Computation and Visualization Software Reference Guide, The MathWorks Inc., 2004
  • [29] Vapnik, V., Estimation of Dependences Based on Empirical Data, 2nd edition, Springer, 2006
  • [30] Kim, D-H., Ship, K. S., Sykulski J. K., Applying continuum design sensitivity analysis combined with standard EM software to shape optimisation in magnetostatic problems, IEEE Trans. Magn., 40 (2004), No. 2, 1156-1159
  • [31] Kim, D-H., Sykulski J. K., Lowther D. A., A novel scheme for material updating in source distribution optimization of magnetic devices using sensitivity analysis, IEEE Trans. Magn., 41 (2005), No. 5, 1752–1755
  • [32] Selected papers from the 9th Workshop on Optimisation and Inverse Problems in Electromagnetism, Sorrento 2006, COMPEL, 26 (2007), No. 2, 229-402
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPOC-0024-0001
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