Abstract
Counting-based branching heuristics such as maxSD were shown to be effective on a variety of constraint satisfaction problems. These heuristics require that we equip each family of constraints with a dedicated algorithm to compute the local solution density of variable assignments, much as what has been done with filtering algorithms to apply local inference. This paper derives an exact polytime algorithm to compute solution densities for a spanning tree constraint, starting from a known result about the number of spanning trees in a graph. We then empirically compare branching heuristics based on that result with other generic heuristics.
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Brockbank, S., Pesant, G., Rousseau, LM. (2013). Counting Spanning Trees to Guide Search in Constrained Spanning Tree Problems. In: Schulte, C. (eds) Principles and Practice of Constraint Programming. CP 2013. Lecture Notes in Computer Science, vol 8124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40627-0_16
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DOI: https://doi.org/10.1007/978-3-642-40627-0_16
Publisher Name: Springer, Berlin, Heidelberg
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