A new cooperative approach to discrete particle swarm optimization

Yiheng Xu, Takayuki Furuzuki, Kotaro Hirasawa, Xiaohong Pang

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

7 Citations (Scopus)

Abstract

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 publicationProceedings of the SICE Annual Conference
Pages1311-1316
Number of pages6
DOIs
Publication statusPublished - 2007
EventSICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007 - Takamatsu
Duration: 2007 Sep 172007 Sep 20

Other

OtherSICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007
CityTakamatsu
Period07/9/1707/9/20

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Keywords

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

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Xu, Y., Furuzuki, T., Hirasawa, K., & Pang, X. (2007). A new cooperative approach to discrete particle swarm optimization. In Proceedings of the SICE Annual Conference (pp. 1311-1316). [4421186] https://doi.org/10.1109/SICE.2007.4421186