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Weight-based Heuristics for Constraint Satisfaction and Combinatorial Optimization Problems

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Journal of Mathematical Modelling and Algorithms

Abstract

In this paper, we propose mechanisms to improve instantiation heuristics by incorporating weighted factors on variables. The proposed weight-based heuristics are evaluated on several tree search methods such as chronological backtracking and discrepancy-based search for both constraint satisfaction and optimization problems. Experiments are carried out on random constraint satisfaction problems, car sequencing problems, and jobshop scheduling with time-lags, considering various parameter settings and variants of the methods.The results show that weighting mechanisms reduce the tree size and then speed up the solving time, especially for the discrepancy-based search method.

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Authors and Affiliations

  1. CNRS, LAAS, 7 avenue du colonel Roche, 31077, Toulouse Cedex 4, France

    Marie-José Huguet, Pierre Lopez & Wafa Karoui

  2. Université de Toulouse, UPS, INSA, INP, ISAE, UT1, UTM, LAAS, 31077, Toulouse, France

    Marie-José Huguet, Pierre Lopez & Wafa Karoui

Authors
  1. Marie-José Huguet
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  2. Pierre Lopez
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  3. Wafa Karoui
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Correspondence to Pierre Lopez.

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Huguet, MJ., Lopez, P. & Karoui, W. Weight-based Heuristics for Constraint Satisfaction and Combinatorial Optimization Problems. J Math Model Algor 11, 193–215 (2012). https://doi.org/10.1007/s10852-012-9174-8

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  • DOI: https://doi.org/10.1007/s10852-012-9174-8

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