A novel chaos glowworm swarm optimization algorithm for optimization functions

  • Authors:

  • Kai Huang;Yong quan Zhou

  • Affiliations:

  • College of Mathematics and Computer Science, Guangxi University for Nationalities, Nanning, Guangxi, China;College of Mathematics and Computer Science, Guangxi University for Nationalities, Nanning, Guangxi, China

  • Venue:
  • ICIC'11 Proceedings of the 7th international conference on Intelligent Computing: bio-inspired computing and applications
  • Year:
  • 2011

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Abstract

This paper a novel chaotic glowworm swarm optimization algorithm (CGSO) is proposed. In CGSO algorithm, the chaotic search strategies are incorporated in GSO to initialize the first iteration solutions, so that it can obtain high-quality and evenly distributed initial solutions, and avoids GSO being trapped in local optima, each glowworm disturbs by chaos in a disturbance range can get more precise global solution. Compared with GSO algorithm, experiments with six test functions shows that convergence quality and precision are improved, which testify that CGSO are valid and feasible.