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Use of Local Ranking in Cellular Genetic Algorithms with Two Neighborhood Structures

  • Hisao Ishibuchi
  • Noritaka Tsukamoto
  • Yusuke Nojima
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5361)

Abstract

In our former study (Ishibuchi et al. 2006), we proposed the use of two neighborhood structures in a cellular genetic algorithm. One is for local selection where a pair of parents is selected from neighboring cells for mating. This neighborhood structure has been usually used in standard cellular algorithms. The other is for local competition, which is used to define local elitism and local ranking. We have already examined the effect of local elitism on the performance of our cellular genetic algorithm (Ishibuchi et al. 2008). In this paper, we examine the effect of using local ranking as the fitness of each individual. First we explain our cellular genetic algorithm with the two neighborhood structures. Then we examine its two variants with/without local ranking. In one variant, the local ranking of an individual among its neighbors is used as its fitness. Such a fitness redefinition scheme can be viewed as a kind of noise in parent selection. The other variant uses the original fitness value (instead of its local ranking). Through computational experiments, we demonstrate that the use of the local ranking improves the ability to escape from local optima.

Keywords

Knapsack Problem Neighborhood Structure Local Selection Local Competition Local Elitism 
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 2008

Authors and Affiliations

  • Hisao Ishibuchi
    • 1
  • Noritaka Tsukamoto
    • 1
  • Yusuke Nojima
    • 1
  1. 1.Department of Computer Science and Intelligent Systems, Graduate School of EngineeringOsaka Prefecture UniversityOsakaJapan

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