A new cooperative approach to discrete particle swarm optimization

Yiheng Xu*, Jinglu Hu, Kotaro Hirasawa, Xiaohong Pang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)


Particle swarm optimization (PSO) is a kind of evolutionary algorithm to find optimal (or near optimal) solutions for numerical and qualitative problems. Recently, a new variation on the traditional PSO algorithm, called cooperative particle swarm optimization (CPSO), has been proposed, employing cooperative behavior to significantly improve the performance of the original algorithm. However, a standard CPSO is focused only on continuous problems. In this paper, we present a new approach based on the CPSO to solve combination optimization problems by introducing dynamic splitting schemes. Reverse operation and simulated annealing techniques are further used to prevent the algorithm from being trapped in local minima. Finally, Traveling salesman problem (TSP) is applied to show the effectiveness of the proposed PSO.

Original languageEnglish
Title of host publicationSICE Annual Conference, SICE 2007
Number of pages6
Publication statusPublished - 2007 Dec 1
EventSICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007 - Takamatsu, Japan
Duration: 2007 Sept 172007 Sept 20

Publication series

NameProceedings of the SICE Annual Conference


ConferenceSICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007


  • Cooperative swarm
  • Dynamic splitting
  • Particle swarm optimization
  • Traveling salesman problem

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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