Particle Evolutionary Swarm Optimization with Linearly Decreasing ε-Tolerance

  • Angel E. Muñoz Zavala
  • Arturo Hernández Aguirre
  • Enrique R. Villa Diharce
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3789)


We introduce the PESO (Particle Evolutionary Swarm Optimization) algorithm for solving single objective constrained optimization problems. PESO algorithm proposes two perturbation operators: “c-perturbation” and “m-perturbation”. The goal of these operators is to prevent premature convergence and the poor diversity issues observed in Particle Swarm Optimization (PSO) implementations. Constraint handling is based on simple feasibility rules, enhanced with a dynamic ε-tolerance approach applicable to equality constraints. PESO is compared and outperforms highly competitive algorithms representative of the state of the art.


Particle Swarm Optimization Equality Constraint Particle Swarm Optimization Algorithm Constraint Handling Reproduction Operator 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Angel E. Muñoz Zavala
    • 1
  • Arturo Hernández Aguirre
    • 1
  • Enrique R. Villa Diharce
    • 1
  1. 1.Department of Computer ScienceCenter for Research in Mathematics (CIMAT)México

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