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Mechanical Design Using Quantum-Behaved Particle Swarm Optimizer With Exponential Mutation Operator

[+] Author Affiliations
Leandro dos Santos Coelho, Viviana Cocco Mariani

Pontifical Catholic University of Paraná

Paper No. IMECE2006-15557, pp. 409-415; 7 pages
doi:10.1115/IMECE2006-15557
From:
  • ASME 2006 International Mechanical Engineering Congress and Exposition
  • Manufacturing Engineering and Textile Engineering
  • Chicago, Illinois, USA, November 5 – 10, 2006
  • Conference Sponsors: Manufacturing Engineering Division and Textile Engineering Division
  • ISBN: 0-7918-4774-8 | eISBN: 0-7918-3790-4
  • Copyright © 2006 by ASME

abstract

Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm that shares many similarities with evolutionary computation techniques. However, the PSO is driven by the simulation of a social psychological metaphor motivated by collective behaviours of bird and other social organisms instead of the survival of the fittest individual. Inspired by the classical PSO method and quantum mechanics theories, this work presents new Quantum-behaved PSO (QPSO) approaches using mutation operator with exponential probability distribution. The simulation results demonstrate good performance of the QPSO in solving a well-studied continuous optimization problem of mechanical engineering design.

Copyright © 2006 by ASME

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