Abstract
This paper introduces directional interchangeability, a weak form of neighborhood interchangeability [6]. The basic idea is that although two values of a variable may not be neighborhood interchangeable if we consider the whole neighborhood of the variable, they could be neighborhood interchangeable if we restrict the neighborhood to a subset of neighboring variables induced by a variable ordering.
In spite of the fact that the proposed concept cannot be used to remove redundant values while preserving problem satisfiability, it provides a mean to partition value domains into subsets of directionally interchangeable values that can be attempted simultaneously by a tree search.
Several experiments carried out on various binary CSPs, clearly indicate that variations of the Forward-Checking algorithm and the Maintaining Arc-Consistency algorithm that exploit directional interchangeability often outperform the original algorithms.
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Naanaa, W. (2007). Directional Interchangeability for Enhancing CSP Solving. In: Van Hentenryck, P., Wolsey, L. (eds) Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. CPAIOR 2007. Lecture Notes in Computer Science, vol 4510. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72397-4_15
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DOI: https://doi.org/10.1007/978-3-540-72397-4_15
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