The particle swarm optimization algorithm in size and shape optimization

  • P.C. Fourie
  • A.A. Groenwold
Research paper

DOI: 10.1007/s00158-002-0188-0

Cite this article as:
Fourie, P. & Groenwold, A. Struct Multidisc Optim (2002) 23: 259. doi:10.1007/s00158-002-0188-0

Abstract.

Shape and size optimization problems instructural design are addressed using the particle swarm optimization algorithm (PSOA). In our implementation of the PSOA, the social behaviour of birds is mimicked. Individual birds exchange information about their position, velocity and fitness, and the behaviour of the flock is then influenced to increase the probability of migration to regions of high fitness. New operators in the PSOA, namely the elite velocity and the elite particle, are introduced.

Standard size and shape design problems selected from literature are used to evaluate the performance of the PSOA. The performance of the PSOA is compared with that of three gradient based methods, as well as the genetic algorithm (GA). In attaining the approximate region of the optimum, our implementation suggests that the PSOA is superior to the GA, and comparable to gradient based algorithms.

Key words: particle swarm optimization, size optimization, shape optimization 

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • P.C. Fourie
    • 1
  • A.A. Groenwold
    • 2
  1. 1.Department of Mechanical Engineering, Technikon Pretoria, Private Bag X680, 0001, Republic of South Africa, e-mail: fouriec@techpta.ac.zaZA
  2. 2.Department of Mechanical Engineering, University of Pretoria, 0002, South Africa e-mail: Albert.Groenwold@eng.up.ac.zaZA

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