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

• Kitayama Satoshi

• Arakawa Masao

• Yamazaki Koetsu

• 北山 哲士

• 荒川 雅生

• 山崎 光悦

抄録

金沢大学理工研究域機械工学系

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. © 2011 Elsevier B.V. All rights reserved.

収録刊行物

• Applied Soft Computing Journal

  Applied Soft Computing Journal 11 (4), 3792-3803, 2011-01-01

  Elsevier B.V.

キーワード

• Differential evolution
• Global optimization
• Structural optimization

詳細情報

• CRID: 1390013795265291648
• NII論文ID: 120002986034
• NII書誌ID: AA11926126
• ISSN: 15684946
• DOI: 10.24517/00007891
• Web Site: http://hdl.handle.net/2297/27308
• 本文言語コード: en
• データソース種別:
  • JaLC
  • IRDB
  • CiNii Articles