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A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimization: NSGA-II

  • Kalyanmoy Deb
  • Samir Agrawal
  • Amrit Pratap
  • T Meyarivan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1917)

Abstract

Multi-objective evolutionary algorithms which use non-dominated sorting and sharing have been mainly criticized for their (i) O(MN 3) computational complexity (where M is the number of objectives and N is the population size), (ii) non-elitism approach, and (iii) the need for specifying a sharing parameter. In this paper, we suggest a non-dominated sorting based multi-objective evolutionary algorithm (we called it the Non-dominated Sorting GA-II or NSGA-II) which alleviates all the above three difficulties. Specifically, a fast non-dominated sorting approach with O(MN 2) computational complexity is presented. Second, a selection operator is presented which creates a mating pool by combining the parent and child populations and selecting the best (with respect to fitness and spread) N solutions. Simulation results on five difficult test problems show that the proposed NSGA-II, in most problems, is able to find much better spread of solutions and better convergence near the true Pareto-optimal front compared to PAES and SPEA—two other elitist multi-objective EAs which pay special attention towards creating a diverse Pareto-optimal front. Because of NSGA-II’s low computational requirements, elitist approach, and parameter-less sharing approach, NSGA-II should find increasing applications in the years to come.

Keywords

Multiobjective Optimization Sharing Parameter Binary Tournament Selection Simulated Binary Crossover Niched Pareto Genetic Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Kalyanmoy Deb
    • 1
  • Samir Agrawal
    • 1
  • Amrit Pratap
    • 1
  • T Meyarivan
    • 1
  1. 1.Kanpur Genetic Algorithms Laboratory (KanGAL)Indian Institute of Technology KanpurKanpurIndia

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