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Simple Linkage Identification Using Genetic Clustering

  • Kei OhnishiEmail author
  • Chang Wook Ahn
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10593)

Abstract

The paper proposes a simple linkage identification method for binary optimization problems. The method is basically equivalent to the genetic clustering method, called GC, inspired by the speciation due to segregation distortion genes that was previously proposed by us. A genetic algorithm using the method, called GAuGC, is also proposed. The GAuGC is applied to decomposable, nearly decomposable, and indecomposable problems. The results show that the GAuGC better solves problems with weak decomposability than the linkage tree genetic algorithm for comparison and also show that it cannot handle the deception well.

Keywords

Genetic algorithm Genetic clustering Linkage identification Data clustering Decomposability 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Kyushu Institute of TechnologyFukuokaJapan
  2. 2.Gwangju Institute of Science and Techology (GIST)GwangjuKorea

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