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Tabu search for maximal constraint satisfaction problems

  • Session 4
  • Conference paper
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Principles and Practice of Constraint Programming-CP97 (CP 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1330))

Abstract

This paper presents a Tabu Search (TS) algorithm for solving maximal constraint satisfaction problems. The algorithm was tested on a wide range of random instances (up to 500 variables and 30 values). Comparisons were carried out with a min-conflicts+random-walk (MCRW) algorithm. Empirical evidence shows that the TS algorithm finds results which are better than that of the MCRW algorithm.the TS algorithm is 3 to 5 times faster than the MCRW algorithm to find solutions of the same quality.

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Authors and Affiliations

  1. LGI2P EMA-EERIE Parc Scientifique Georges Besse, F-30000, Nimes, France

    Philippe Galinier & Jin-Kao Hao

Authors
  1. Philippe Galinier
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  2. Jin-Kao Hao
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Gert Smolka

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© 1997 Springer-Verlag Berlin Heidelberg

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Galinier, P., Hao, JK. (1997). Tabu search for maximal constraint satisfaction problems. In: Smolka, G. (eds) Principles and Practice of Constraint Programming-CP97. CP 1997. Lecture Notes in Computer Science, vol 1330. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0017440

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  • DOI: https://doi.org/10.1007/BFb0017440

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63753-0

  • Online ISBN: 978-3-540-69642-1

  • eBook Packages: Springer Book Archive

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