A Particle Swarm Optimizer for Constrained Numerical Optimization

  • Leticia C. Cagnina
  • Susana C. Esquivel
  • Carlos A. Coello Coello
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4193)


This paper presents a particle swarm optimizer to solve constrained optimization problems. The proposed approach adopts a simple method to handle constraints of any type (linear, nonlinear, equality and inequality), and it also presents a novel mechanism to update the velocity and position of each particle. The approach is validated using standard test functions reported in the specialized literature and it’s compared with respect to algorithms representative of the state-of-the-art in the area. Our results indicate that the proposed scheme is a promising alternative to solve constrained optimization problems using particle swarm optimization.


Particle Swarm Optimization Particle Swarm Constrain Optimization Problem Current Cycle Objective Function Evaluation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Leticia C. Cagnina
    • 1
  • Susana C. Esquivel
    • 1
  • Carlos A. Coello Coello
    • 2
  1. 1.LIDIC (Research Group)Universidad Nacional de San LuisSan LuisArgentina
  2. 2.Computer Science SectionCINVESTAV-IPN (Evolutionary Computation Group)Mexico D.F.Mexico

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