Distributed probabilistic model-building genetic algorithm

Tomoyuki Hiroyasu, Mitsunori Miki, Masaki Sano, Hisashi Shimosaka, Shigeyoshi Tsutsui, Jack Dongarra

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

In this paper, a new model of Probabilistic Model-Building Genetic Algorithms (PMBGAs), Distributed PMBGA (DPMBGA), is proposed. In the DPMBGA, the correlation among the design variables is considered by Principal Component Analysis (PCA) when the offsprings are generated. The island model is also applied in the DPMBGA for maintaining the population diversity. Through the standard test functions, some models of DPMBGA are examined. The DPMBGA where PCA is executed in the half of the islands can find the good solutions in the problems whether or not the problems have the correlation among the design variables. At the same time, the search capability and some characteristics of the DPMBGA are also discussed.

Original languageEnglish
Pages (from-to)1015-1028
Number of pages14
JournalLecture Notes in Computer Science
Volume2723
DOIs
StatePublished - 2003
Externally publishedYes

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