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Hybrid Extremal Optimization and Glowworm Swarm Optimization

  • Niusha Ghandehari
  • Elham Miranian
  • Mojtaba Maddahi
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 150)

Abstract

Glowworm Swarm Optimization algorithm is applied for the simultaneous capture of multiple optima of multimodal functions. In this paper, we have attempted to create a Hybrid Extremal Glowworm Swarm Optimization (HEGSO) algorithm. Aiming at the glowworm swarm optimization algorithm is easy to fall into local optima, having low accuracy, and to be unable to find the best local optima. However for solving these problems, the present algorithm has been increased the probability of choosing the best local optima. Moreover we want to use this method to have a best movement for agents in Glow worm optimization algorithm. Simulation and comparison based on several well-studied benchmarks demonstrate the effectiveness, efficiency and robustness of the proposed algorithms.

Keywords

Extremal optimization Glowworm swarm optimization Hybrid algorithm 

References

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Niusha Ghandehari
    • 1
  • Elham Miranian
    • 1
  • Mojtaba Maddahi
    • 1
  1. 1.Department of Information TechnologySufi Razi Institute of Higher EducationZanjanIran

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