Abstract
A binary constraints network consists of a set of n variables, defined on domains of size at most d, and a set of e binary constraints. The binary constraint satisfaction problem consists in finding a solution for a binary constraints network, that is an instantiation of all the variables which satisfies all the constraints. A value a in the domain of variable x is inconsistent if there is no solution which assigns a to x. Many filtering techniques have been proposed to filter out inconsistent values from the domains. Most of them are based on enforcing a given kind of local consistency. One of the most important such consistencies is max-restricted path consistency. The fastest algorithm to enforce max-restricted path consistency has a O (end 3) time complexity and a O (end) space complexity. In this paper we present two improved algorithms for the same problem. The first still has a O (end 3) time complexity, but it reduces the space usage to O (ed). The second improves the time complexity to O (end 2.575), and has a O (end 2) space complexity.
This work has been partially supported by the IST Programme of the EU under contract n. IST-1999-14.186 (ALCOM-FT), by the Italian Ministry of University and Research (Project “ALINWEB: Algorithmics for Internet and the Web”).
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© 2003 Springer-Verlag Berlin Heidelberg
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Grandoni, F., Italiano, G.F. (2003). Improved Algorithms for Max-restricted Path Consistency. In: Rossi, F. (eds) Principles and Practice of Constraint Programming – CP 2003. CP 2003. Lecture Notes in Computer Science, vol 2833. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45193-8_67
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DOI: https://doi.org/10.1007/978-3-540-45193-8_67
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