Multi-objective PSO Algorithm Based on Fitness Sharing and Online Elite Archiving

  • Li Wang
  • Yushu Liu
  • Yuanqing Xu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4113)


A new technique for multi-objective PSO (Particle Swarm Optimization) based on fitness sharing and online elite archiving is proposed. Global best position of particle swarm is selected from repository by fitness sharing, which guarantees the diversity of the population. At the same time, in order to ensure the excellent population, the elite particles from the repository are introduced into next iteration. Three well-known test functions taken from the multi-objective optimization literature are used to evaluate the performance of the proposed approach. The results indicate that our approach generates a satisfactory approximation of the Pareto front and spread widely along the front.


Pareto Front Multiobjective Optimization Pareto Optimal Front Decision Vector Fitness Sharing 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Li Wang
    • 1
  • Yushu Liu
    • 1
  • Yuanqing Xu
    • 2
  1. 1.School of Computer Science and TechnologyBeijing Institute of TechnologyBeijingChina
  2. 2.School of Chemical Engineering and EnvironmentBeijing Institute of TechnologyBeijingChina

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