Improving the non-dominate sorting genetic algorithm for multi-objective optimization

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  • Vahid Seydi
    Azad University
  • M Ahmadieh Khanehsar
  • M Teshnehlab
The non-dominate sorting genetic algorithmic-II (NSGA-II) is a relatively recent technique for finding or approximating the Pareto-optimal set for multi-objective optimization problems. In different studies NSGA-II has shown good performance in comparison to other multi-objective evolutionary algorithms (Deb et al., 2002). In this paper an improved version which is named Niching-NSGA-II (n-NSGA-II) is proposed. This algorithm uses new method after non-dominate sorting procedure for keeping diversity. The comparison of n-NSGA-II with NSGA-II and other methods on ZDT test problems yields promising results.
Original languageEnglish
Title of host publication2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007)
Number of pages4
Publication statusPublished - 2007
Externally publishedYes
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