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Heuristic techniques for variable and value ordering in CSPs

Published: 12 July 2011 Publication History

Abstract

A Constraint Satisfaction Problem (CSP) is a powerful framework for representing and solving constraint problems. When solving a CSP using a backtrack search method, one important factor that reduces the size of the search space drastically is the order in which variables and values are examined. Many heuristics for static and dynamic variable ordering have been proposed and the most popular and powerful are those that gather information about the failures during the constraint propagation phase, in the form of constraint weights. These later heuristics are called conflict driven heuristics. In this paper, we propose two of these heuristics respectively based on Hill Climbing (HC) and Ant Colony Optimization (ACO) for weighing constraints. In addition, we propose two new value ordering techniques, respectively based on HC and ACO, that rank the values based on their ability to satisfy the constraints attached to their corresponding variables. Several experiments were conducted on various types of problems including random, quasi random and patterned problems. The results show that the proposed variable ordering heuristics, are successful especially in the case of hard random problems. Also, when using the proposed value and variable ordering together, we can improve the performance particularly in the case of random problems.

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cover image ACM Conferences
GECCO '11: Proceedings of the 13th annual conference on Genetic and evolutionary computation
July 2011
2140 pages
ISBN:9781450305570
DOI:10.1145/2001576
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 12 July 2011

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Author Tags

  1. ant colony optimization (aco)
  2. constraint satisfaction problems (csps)
  3. hill climbing (hc)
  4. variable ordering.

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  • (2022)Mother Tree Optimization for Conditional Constraints and Qualitative Preferences2022 IEEE Symposium Series on Computational Intelligence (SSCI)10.1109/SSCI51031.2022.10022070(1610-1617)Online publication date: 4-Dec-2022
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