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Particle Swarm Optimization with Dynamic Parameter Adaptation Using Fuzzy Logic for Benchmark Mathematical Functions

  • Frumen Olivas
  • Oscar Castillo
Part of the Studies in Computational Intelligence book series (SCI, volume 451)

Abstract

In this paper a new method for dynamic parameter adaptation in particle swarm optimization (PSO) is proposed. PSO is a metaheuristic inspired in social behaviors, which is very useful in optimization problems. In this paper we propose an improvement to the convergence and diversity of the swarm in PSO using fuzzy logic. Simulation results show that the proposed approach improves the performance of PSO.

Keywords

Fuzzy Logic Particle Swarm Optimization Dynamic parameter adaptation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Frumen Olivas
    • 1
  • Oscar Castillo
    • 1
  1. 1.Tijuana Institute of TechnologyTijuanaMéxico

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