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Journal of Intelligent Manufacturing

, Volume 14, Issue 3–4, pp 401–419 | Cite as

Various hybrid methods based on genetic algorithm with fuzzy logic controller

  • Youngsu Yun
  • Mitsuo Gen
  • Seunglock Seo
Article

Abstract

In this paper we propose several efficient hybrid methods based on genetic algorithms and fuzzy logic. The proposed hybridization methods combine a rough search technique, a fuzzy logic controller, and a local search technique. The rough search technique is used to initialize the population of the genetic algorithm (GA), its strategy is to make large jumps in the search space in order to avoid being trapped in local optima. The fuzzy logic controller is applied to dynamically regulate the fine-tuning structure of the genetic algorithm parameters (crossover ratio and mutation ratio). The local search technique is applied to find a better solution in the convergence region after the GA loop or within the GA loop. Five algorithms including one plain GA and four hybrid GAs along with some conventional heuristics are applied to three complex optimization problems. The results are analyzed and the best hybrid algorithm is recommended.

Hybrid algorithm genetic algorithm fuzzy logic controller and local search technique 

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Copyright information

© Kluwer Academic Publishers 2003

Authors and Affiliations

  • Youngsu Yun
    • 1
  • Mitsuo Gen
    • 2
  • Seunglock Seo
    • 1
  1. 1.School of Automotive, Industrial & Mechanical EngineeringDaegu UniversityKyungbookKorea
  2. 2.Graduate School of Information, Production & SystemsWaseda UniversityKitakyushuJapan

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