An improved discrete particle swarm optimization based on cooperative swarms

Yiheng Xu, Qiangwei Wang, Takayuki Furuzuki

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

9 Citations (Scopus)

Abstract

The discrete particle swarm optimization (DPSO) is a kind of particle swarm optimization (PSO) algorithm to find optimal solutions for discrete problems. This paper proposes an improved DPSO based on cooperative swarms, which partition the search space into lower dimensional subspaces. The k-means split scheme and regular split scheme are applied to split the solution vector into swarms. Then the swarms optimize the different components of the solution vector cooperatively. Some strategies are further used to improve the accuracy and convergence. Application of the proposed cooperative swarms based DPSO (CDPSO) on the traveling salesman problem (TSP) shows a significant improvement over conventional DPSOs.

Original languageEnglish
Title of host publicationProceedings - 2008 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2008
Pages79-82
Number of pages4
DOIs
Publication statusPublished - 2008
Event2008 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2008 - Sydney, NSW
Duration: 2008 Dec 92008 Dec 12

Other

Other2008 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2008
CitySydney, NSW
Period08/12/908/12/12

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ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

Cite this

Xu, Y., Wang, Q., & Furuzuki, T. (2008). An improved discrete particle swarm optimization based on cooperative swarms. In Proceedings - 2008 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2008 (pp. 79-82). [4740600] https://doi.org/10.1109/WIIAT.2008.103