Novel Fish Swarm Heuristics for Bound Constrained Global Optimization Problems

  • Ana Maria A. C. Rocha
  • Edite M. G. P. Fernandes
  • Tiago F. M. C. Martins
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6784)


The heuristics herein presented are modified versions of the artificial fish swarm algorithm for global optimization. The new ideas aim to improve solution accuracy and reduce computational costs, in particular the number of function evaluations. The modifications also focus on special point movements, such as the random, search and the leap movements. A local search is applied to refine promising regions. An extension to bound constrained problems is also presented. To assess the performance of the two proposed heuristics, we use the performance profiles as proposed by Dolan and Moré in 2002. A comparison with three stochastic methods from the literature is included.


Global optimization Derivative-free method Swarm intelligence Heuristics 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ana Maria A. C. Rocha
    • 1
  • Edite M. G. P. Fernandes
    • 2
  • Tiago F. M. C. Martins
    • 2
  1. 1.Department of Production and SystemsUniversity of MinhoBragaPortugal
  2. 2.Algoritmi R&D CentreUniversity of MinhoBragaPortugal

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