Abstract
Many real life problems can be modeled as constraint satisfaction problems (CSPs) and be solved using constraint programming techniques. In broad domains, consistency techniques become an important issue important since they can prune the search space and make more efficient the search of solutions. In this paper, we present AC2001-OP, an optimized version of AC2001/3.1 for arithmetic constraints, that reduces the number of propagations, the number of constraint checks and the running time meanwhile it prunes the same search space that the standard version. In inequality constraints, AC2001-OP, checks the binary constraints in both directions (full arc-consistency), but it only propagates the new constraints in one direction. Thus, it avoids checking redundant constraints that do not filter any value of variable’s domains. The computational evaluation performed shows the improvement of AC2001-OP over AC2001/3.1 in both random instances as well as in domain-oriented problems of railway scheduling scenarios.
This work has been partially supported by the research projects TIN2007-67943-C02-01 (Min. de Educacion y Ciencia, Spain-FEDER) and P19/08 (Min. de Fomento, Spain-FEDER).
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Arangú, M., Salido, M.A., Barber, F. (2010). AC2001-OP: An Arc-Consistency Algorithm for Constraint Satisfaction Problems. In: García-Pedrajas, N., Herrera, F., Fyfe, C., Benítez, J.M., Ali, M. (eds) Trends in Applied Intelligent Systems. IEA/AIE 2010. Lecture Notes in Computer Science(), vol 6098. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13033-5_23
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DOI: https://doi.org/10.1007/978-3-642-13033-5_23
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