Decision and optimization problems can be tackled with different techniques, such as Mixed Integer Programming, Constraint Programming or SAT solving. An important ingredient in the success of each of these approaches is the exploitation of common constraint structures with specialized (re-)formulations, encodings or other techniques. In this paper we present a new linear SAT encoding using binary decision diagrams over multiple variable orders as intermediate representation of a special form of constraints denoted as staircase at-most-one-constraints. The use of these constraints is motivated by recent work on the antibandwidth problem, where an iterative solution procedure using feasibility-mixed integer programs based on such constraints was most effective. In a computational study we compare the effectiveness of our new encoding against traditional SAT-encodings for staircase at-most-one-constraints. Additionally we compare against previous exact solution methods for the antibandwidth problem, such as a constraint programming approach and the one based on feasibility-mixed integer programs.
CITATION STYLE
Fazekas, K., Sinnl, M., Biere, A., & Parragh, S. (2020). Duplex Encoding of Staircase At-Most-One Constraints for the Antibandwidth Problem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12296 LNCS, pp. 186–204). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-58942-4_13
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