DocumentCode :
3046896
Title :
Multi-objective Integrated Optimization Using Optimization, Modeling and Simulation
Author :
Katayama, Hiromi ; Tamura, Keiichi ; Yasuda, Kazuhiro
Author_Institution :
Dept. of Electr. & Electron. Eng., Tokyo Metropolitan Univ., Hachioji, Japan
fYear :
2013
fDate :
13-16 Oct. 2013
Firstpage :
3537
Lastpage :
3542
Abstract :
In this paper, the authors propose a new practical multi-objective optimization framework that combines optimization method, modeling and simulation technologies organically. The new framework is called Multi-Objective Integrated Optimization that combines Multi-Objective Differential Evolution and Radial Basis Function Network. This new framework is used to reduce the number of accesses to a simulator or a sensing system with heavy computational load. According to the numerical experiment on typical benchmark problems, it is shown that the proposed Multi-Objective Integrated Optimization obtains good Pareto solutions with drastic reduction in the number of function calls for evaluating the performance index values of systems.
Keywords :
Pareto optimisation; evolutionary computation; modelling; performance index; radial basis function networks; simulation; Pareto solutions; computational load; function calls; modeling; multiobjective differential evolution; multiobjective integrated optimization; multiobjective optimization framework; optimization method; performance index values; radial basis function network; sensing system; simulation technologies; Accuracy; Computational modeling; Mathematical model; Numerical models; Optimization methods; Response surface methodology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
Conference_Location :
Manchester
Type :
conf
DOI :
10.1109/SMC.2013.603
Filename :
6722356
Link To Document :
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