Abstract
This paper furthers the recent investigation of search heuristics based on solution counting information, by proposing and evaluating algorithms to compute solution densities of variable-value pairs in knapsack constraints. Given a domain consistent constraint, our first algorithm is inspired from what was proposed for regular language membership constraints. Given a bounds consistent constraint, our second algorithm draws from discrete uniform distributions. Experiments on several problems reveal that simple search heuristics built from the information obtained by these algorithms can be very effective.
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Pesant, G., Quimper, CG. (2008). Counting Solutions of Knapsack Constraints. In: Perron, L., Trick, M.A. (eds) Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. CPAIOR 2008. Lecture Notes in Computer Science, vol 5015. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68155-7_17
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DOI: https://doi.org/10.1007/978-3-540-68155-7_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68154-0
Online ISBN: 978-3-540-68155-7
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