A Hybrid Evolutionary Algorithm for Global Optimization

  • Mend-Amar MajigEmail author
  • Abdel-Rahman Hedar
  • Masao Fukushima
Part of the Springer Optimization and Its Applications book series (SOIA, volume 39)


In this work, we propose a method for finding as many as possible, hopefully all, solutions of the global optimization problem. For this purpose, we hybridize an evolutionary search algorithm with a fitness function modification procedure. Moreover, to make the method more effective, we employ some local search method and a special procedure to detect unpromising trial solutions. Numerical results for some well-known global optimization test problems show the method works well in practice.


global optimization tunneling function evolutionary algorithm local search 


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Mend-Amar Majig
    • 1
    Email author
  • Abdel-Rahman Hedar
    • 1
  • Masao Fukushima
    • 1
  1. 1.Department of Applied Mathematics and Physics, Graduate School of InformaticsKyoto UniversityKyotoJapan

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