Design optimization with chaos embedded great deluge algorithm

Baykasoglu A.

APPLIED SOFT COMPUTING, cilt.12, sa.3, ss.1055-1067, 2012 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 12 Sayı: 3
  • Basım Tarihi: 2012
  • Doi Numarası: 10.1016/j.asoc.2011.11.018
  • Dergi Adı: APPLIED SOFT COMPUTING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1055-1067
  • Anahtar Kelimeler: Great deluge algorithm, Chaotic maps, Design optimization, Non-linear programming, PARTICLE SWARM OPTIMIZATION, GENETIC ALGORITHMS, SEARCH, PERFORMANCE, SIMULATION, MECHANISM, MODELS, MAPS
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

In this paper, the great deluge algorithm (GDA), which has not been previously used in constrained mechanical design optimization problems is employed to solve several design optimization problems selected from the literature. The GDA algorithm needs only one basic parameter to setup, which makes it very attractive for solving optimization problems. First time in this paper, an attempt is made to see whether it is possible to enhance the performance of a very simple algorithm like GDA to solve complex constrained non-linear design optimization problems by embedding chaotic maps in its neighborhood generation mechanism. Eight different chaotic maps are tested and compared in this paper. It is observed that chaotic maps can considerably improve the performance of GDA and enables it to find the best possible solutions for the studied problems. (C) 2011 Elsevier B.V. All rights reserved.