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  • 标题:Probabilistic Model Building Based GAs in Permutation Domains Using Edge Histograms
  • 本地全文:下载
  • 作者:Shigeyoshi Tsutsui
  • 期刊名称:人工知能学会論文誌
  • 印刷版ISSN:1346-0714
  • 电子版ISSN:1346-8030
  • 出版年度:2003
  • 卷号:18
  • 期号:4
  • 页码:173-182
  • DOI:10.1527/tjsai.18.173
  • 出版社:The Japanese Society for Artificial Intelligence
  • 摘要:Recently, there has been a growing interest in developing evolutionary algorithms based on probabilistic modeling. They are called probabilistic model-building genetic algorithms (PMBGAs) or estimation of distribution algorithms (EDAs). In this scheme, the offspring population is generated according to the estimated probability density model of the parent instead of using recombination and mutation operators. In this paper, we have proposed PMBGAs in permutation domains using edge histogram based sampling algorithms (EHBSAs). Two types of sampling algorithms, without template (EHBSA/WO) and with template (EHBSA/WT), are presented. The results were tested in the TSP and showed EHBSA/WT worked fairly well with a small population size in the test problems used. It also worked better than well-known traditional two-parent recombination operators.
  • 关键词:PMBGAs (probabilistic model building based GAs) ; EDAs (estimation of distribution algorithms) ; edge histogram ; EHBSA (edge histogram based sampling algorithm)
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