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Impact-Based Search Strategies for Constraint Programming

  • Conference paper
Principles and Practice of Constraint Programming – CP 2004 (CP 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3258))

Abstract

A key feature of constraint programming is the ability to design specific search strategies to solve problems. On the contrary, integer programming solvers have used efficient general-purpose strategies since their earliest implementations. We present a new general purpose search strategy for constraint programming inspired from integer programming techniques and based on the concept of the impact of a variable. The impact measures the importance of a variable for the reduction of the search space. Impacts are learned from the observation of domain reduction during search and we show how restarting search can dramatically improve performance. Using impacts for solving multiknapsack, magic square, and Latin square completion problems shows that this new criteria for choosing variables and values can outperform classical general-purpose strategies.

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Author information

Authors and Affiliations

  1. ILOG, Les Taissounieres, 1681, route des Dolines, 06560, Sophia Antipolis, France

    Philippe Refalo

Authors
  1. Philippe Refalo
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Editor information

Editors and Affiliations

  1. Clayton School of IT, Monash University, Australia

    Mark Wallace

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© 2004 Springer-Verlag Berlin Heidelberg

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Refalo, P. (2004). Impact-Based Search Strategies for Constraint Programming. In: Wallace, M. (eds) Principles and Practice of Constraint Programming – CP 2004. CP 2004. Lecture Notes in Computer Science, vol 3258. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30201-8_41

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  • DOI: https://doi.org/10.1007/978-3-540-30201-8_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23241-4

  • Online ISBN: 978-3-540-30201-8

  • eBook Packages: Springer Book Archive

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