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Improving NSGA-II Algorithm Based on Minimum Spanning Tree

  • Miqing Li
  • Jinhua Zheng
  • Jun Wu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5361)

Abstract

Diversity maintenance is an importance part of multi-objective evolutionary algorithm. In this paper, a new variant for the NSGA-II algorithm is proposed. The basic idea is that using the crowding distance method designed by minimum spanning tree to maintain the distribution of solutions. From an extensive comparative study with NSGA-II on a number of two and three objective test problems, it is observed that the proposed algorithm has good performance in distribution, and is also rather competitive to NSGA-II concerning the convergence.

Keywords

Multi-objective optimization Multi-objective evolutionary algorithm Crowding distance Minimum spanning tree 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Miqing Li
    • 1
  • Jinhua Zheng
    • 1
  • Jun Wu
    • 1
  1. 1.Institute of Information EngineeringXiangtan UniversityHunanChina

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