An Island Based Hybrid Evolutionary Algorithm for Optimization

  • Changhe Li
  • Shengxiang Yang
Conference paper

DOI: 10.1007/978-3-540-89694-4_19

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5361)
Cite this paper as:
Li C., Yang S. (2008) An Island Based Hybrid Evolutionary Algorithm for Optimization. In: Li X. et al. (eds) Simulated Evolution and Learning. SEAL 2008. Lecture Notes in Computer Science, vol 5361. Springer, Berlin, Heidelberg

Abstract

Evolutionary computation has become an important problem solving methodology among the set of search and optimization techniques. Recently, more and more different evolutionary techniques have been developed, especially hybrid evolutionary algorithms. This paper proposes an island based hybrid evolutionary algorithm (IHEA) for optimization, which is based on Particle swarm optimization (PSO), Fast Evolutionary Programming (FEP), and Estimation of Distribution Algorithm (EDA). Within IHEA, an island model is designed to cooperatively search for the global optima in search space. By combining the strengths of the three component algorithms, IHEA greatly improves the optimization performance of the three basic algorithms. Experimental results demonstrate that IHEA outperforms all the three component algorithms on the test problems.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Changhe Li
    • 1
  • Shengxiang Yang
    • 1
  1. 1.Department of Computer ScienceUniversity of LeicesterLeicesterUK

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