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An Improved Glowworm Swarm Optimization Algorithm Based on Parallel Hybrid Mutation

  • Zhonghua Tang
  • Yongquan Zhou
  • Xin Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7996)

Abstract

Glowworm swarm optimization (GSO) algorithm is a novel algorithm based on swarm intelligence and inspired from light emission behavior of glowworms to attract a peer or prey in nature. The main application of this algorithm is to capture all local optima of multimodal function. GSO algorithm has shown some such weaknesses in global search as low accuracy computation and easy to fall into local optimum. In order to overcome above disadvantages of GSO, this paper presented an improved GSO algorithm, which called parallel hybrid mutation glowworm swarm optimization (PHMGSO) algorithm. Experimental results show that PHMGSO has higher calculation accuracy and convergence faster speed compared to standard GSO and PSO algorithms.

Keywords

GSO PSO Hybrid Mutation Global Search 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Zhonghua Tang
    • 1
  • Yongquan Zhou
    • 1
    • 2
  • Xin Chen
    • 1
  1. 1.College of Information Science and EngineeringGuangxi University for NationalitiesNanningChina
  2. 2.Guangxi Key Laboratory of Hybrid Computation and IC Design AnalysisNanningChina

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