Differential evolution as the global optimization technique and its application to structural optimization

In this paper, the basic characteristics of the differential evolution (DE) are examined. Thus, one is the meta-heuristics, and the other is the global optimization technique. It is said that DE is the global optimization technique, and also belongs to the meta-heuristics. Indeed, DE can find the gl...

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Bibliographic Details
Published inApplied soft computing Vol. 11; no. 4; pp. 3792 - 3803
Main Authors Kitayama, Satoshi, Arakawa, Masao, Yamazaki, Koetsu
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.06.2011
Subjects
Differential evolution
Global optimization
Structural optimization
Structural optimization
Differential evolution
Global optimization
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ISSN1568-4946
1872-9681
DOI10.1016/j.asoc.2011.02.012

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Summary:In this paper, the basic characteristics of the differential evolution (DE) are examined. Thus, one is the meta-heuristics, and the other is the global optimization technique. It is said that DE is the global optimization technique, and also belongs to the meta-heuristics. Indeed, DE can find the global minimum through numerical experiments. However, there are no proofs and useful investigations with regard to such comments. In this paper, the DE is compared with the generalized random tunneling algorithm (GRTA) and the particle swarm optimization (PSO) that are the global optimization techniques for continuous design variables. Through the examinations, some common characteristics as the global optimization technique are clarified in this paper. Through benchmark test problems including structural optimization problems, the search ability of DE as the global optimization technique is examined.
ISSN:1568-4946
1872-9681
DOI:10.1016/j.asoc.2011.02.012