Comparison of evolutionary-based optimization algorithms for structural design optimization

Yildiz A. R.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, vol.26, no.1, pp.327-333, 2013 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 26 Issue: 1
  • Publication Date: 2013
  • Doi Number: 10.1016/j.engappai.2012.05.014
  • Journal Name: ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.327-333
  • Keywords: Structural design, Differential evolution, Hybrid Optimization, Taguchi method, Welded beam, Vehicle component, PARTICLE SWARM OPTIMIZATION, DIFFERENTIAL EVOLUTION, GENETIC ALGORITHM, HYBRID, SEARCH
  • Bursa Uludag University Affiliated: Yes

Abstract

In this paper, a comparison of evolutionary-based optimization techniques for structural design optimization problems is presented. Furthermore, a hybrid optimization technique based on differential evolution algorithm is introduced for structural design optimization problems. In order to evaluate the proposed optimization approach a welded beam design problem taken from the literature is solved. The proposed approach is applied to a welded beam design problem and the optimal design of a vehicle component to illustrate how the present approach can be applied for solving structural design optimization problems. A comparative study of six population-based optimization algorithms for optimal design of the structures is presented. The volume reduction of the vehicle component is 28.4% using the proposed hybrid approach. The results show that the proposed approach gives better solutions compared to genetic algorithm, particle swarm, immune algorithm, artificial bee colony algorithm and differential evolution algorithm that are representative of the state-of-the-art in the evolutionary optimization literature. (C) 2012 Elsevier Ltd. All rights reserved.