Searching under Multi-evolutionary Pressures

  • Hussein A. Abbass
  • Kalyanmoy Deb
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2632)

Abstract

A number of authors made the claim that a multiobjective approach preserves genetic diversity better than a single objective approach. Sofar, none of these claims presented a thorough analysis to the effect of multiobjective approaches. In this paper, we provide such analysis and show that a multiobjective approach does preserve reproductive diversity. We make our case by comparing a pareto multiobjective approach against a single objective approach for solving single objective global optimization problems in the absence of mutation. We show that the fitness landscape is different in both cases and the multiobjective approach scales faster and produces better solutions than the single objective approach.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Hussein A. Abbass
    • 1
  • Kalyanmoy Deb
    • 2
  1. 1.Artifficial Life and Adaptive Robotics (A.L.A.R.) Lab, School of Computer ScienceUniversity of New South Wales, Australian Defence Force Academy CampusCanberraAustralia
  2. 2.Mechanical Engineering DepartmentIndian Institute of Technology, KanpurKanpurIndia

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