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International Conference on Parallel Problem Solving from Nature

PPSN 2002: Parallel Problem Solving from Nature — PPSN VII pp 224–233Cite as

Probabilistic Model-Building Genetic Algorithms in Permutation Representation Domain Using Edge Histogram

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2439))

Abstract

Recently, there has been a growing interest in developing evolutionary algorithms based on probabilistic modeling. 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 probabilistic model-building genetic algorithms (PMBGAs) in permutation representation domain 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.

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Authors and Affiliations

  1. Department of Management and Information Science, Hannan University, 5-4-33 Amamihigashi, Matsubara, 580-5802, Osaka, Japan

    Shigeyoshi Tsutsui

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  1. Shigeyoshi Tsutsui
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Editors and Affiliations

  1. Escuela Técnica Superior de Ingeniería Informática, 18071, Granada, Spain

    Juan Julián Merelo Guervós

  2. Department of Informatics, Technological Educational Institute of Thessaloniki, 54101, Thessaloniki, Greece

    Panagiotis Adamidis

  3. Department of Informatics XI, University of Dortmund, 44221, Dortmund, Germany

    Hans-Georg Beyer  & Hans-Paul Schwefel  & 

  4. Department of Signal Theory and Communications, Universidad Carlos III, Madrid, Spain

    José-Luis Fernández-Villacañas

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© 2002 Springer-Verlag Berlin Heidelberg

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Tsutsui, S. (2002). Probabilistic Model-Building Genetic Algorithms in Permutation Representation Domain Using Edge Histogram. In: Guervós, J.J.M., Adamidis, P., Beyer, HG., Schwefel, HP., Fernández-Villacañas, JL. (eds) Parallel Problem Solving from Nature — PPSN VII. PPSN 2002. Lecture Notes in Computer Science, vol 2439. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45712-7_22

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  • DOI: https://doi.org/10.1007/3-540-45712-7_22

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44139-7

  • Online ISBN: 978-3-540-45712-1

  • eBook Packages: Springer Book Archive

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