DocumentCode
593918
Title
Pure and Hybrid Optimizers Applicable to Large-Scale Design Problem
Author
Chiba, Kazuya
Author_Institution
Dept. of Mech. Syst. Eng., Hokkaido Inst. of Technol., Sapporo, Japan
fYear
2012
fDate
25-28 Aug. 2012
Firstpage
409
Lastpage
412
Abstract
Design-Informatics has three points of view. One of these points is the investigation of efficient optimization to generate hypothetical database for a large-scale design problem. the results of the present study indicates the hybrid method between differential evolution and genetic algorithm is better performance for efficient exploration in design space under the condition for large-scale engineering design problem within 102 order evolution at most.
Keywords
design engineering; genetic algorithms; particle swarm optimisation; design-informatics; differential evolution; genetic algorithm; hybrid optimizers; large-scale engineering design problem; particle swarm optimization; pure optimizers; Evolutionary computation; Genetic algorithms; History; Measurement; Noise; Optimization; Sociology; design-informatics; differential evolution; evolutionary computation; genetic algorithm; hybrid optimizer; particle swarm optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Genetic and Evolutionary Computing (ICGEC), 2012 Sixth International Conference on
Conference_Location
Kitakushu
Print_ISBN
978-1-4673-2138-9
Type
conf
DOI
10.1109/ICGEC.2012.123
Filename
6457132
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