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Evaluating Migration Strategies for an Evolutionary Algorithm Based on the Constraint-Graph that Solves CSP

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Foundations of Intelligent Systems (ISMIS 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1932))

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Abstract

Constraint satisfaction problems (CSPs) occur widely in ar- tificial intelligence. In the last twenty years, many algorithms and heuristics were developed to solve CSP. Recently, a constraint-graph based evolutionary algorithm was proposed to solve CSP, [17]. It shown that it is advantageous to take into account the knowledge of the constraint network to design genetic operators. On the other hand, recent publications indicate that parallel genetic algorithms (PGA’s) with isolated evolving subpopulations (that exchange individuals from time to time) may offer advantages over sequential approaches, [1]. In this paper we examine the gain of the performance obtained using multiple populations — that evolve in parallel — of the constraint-graph based evolutionary algorithm with a migration policy. We show that a multiple populations approach outperforms a single population implementation when applying it to the 3-coloring problem.

Partially supported by the Research Department Grant at University Santa María, Chile

Supported by the Computer Science Department LIP6 at the Université Pierre et Marie Curie, France. e-mail: Maria-Cristina.Riff@lip6.fr

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Author information

Authors and Affiliations

  1. Computer Science Department, Universidad Técnica Federico Santa María, Valparaío, Chile

    Arturo NÚñez & María-Cristina Riff

Authors
  1. Arturo NÚñez
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  2. María-Cristina Riff
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Editor information

Editors and Affiliations

  1. Institute of Computer Science, Polish Academy of Sciences, 01-237, Warsaw, Poland

    Zbigniew W. Raś

  2. Department of Computer Science, University of North Carolina, NC 28223, Charlotte, USA

    Zbigniew W. Raś

  3. Department of Science and Technology, Waseda University, 61-414, 3-4-1, Ohkubo, Shinjuku-ku, 169-8555, Tokyo, Japan

    Setsuo Ohsuga

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NÚñez, A., Riff, MC. (2000). Evaluating Migration Strategies for an Evolutionary Algorithm Based on the Constraint-Graph that Solves CSP. In: Raś, Z.W., Ohsuga, S. (eds) Foundations of Intelligent Systems. ISMIS 2000. Lecture Notes in Computer Science(), vol 1932. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39963-1_21

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  • DOI: https://doi.org/10.1007/3-540-39963-1_21

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41094-2

  • Online ISBN: 978-3-540-39963-6

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