Automatic discovery and exploitation of promising subproblems for tabulation
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The performance of a constraint model can often be improved by converting a subproblem into a single table constraint. In this paper we study heuristics for identifying promising subproblems. We propose a small set of heuristics to identify common cases such as expressions that will propagate weakly. The process of discovering promising subproblems and tabulating them is entirely automated in the tool Savile Row. A cache is implemented to avoid tabulating equivalent subproblems many times. We give a simple algorithm to generate table constraints directly from a constraint expression in Savile Row. We demonstrate good performance on the benchmark problems used in earlier work on tabulation, and also for several new problem classes.
Akgun , O , Gent , I P , Jefferson , C A , Miguel , I J , Nightingale , P W & Salamon , A Z 2018 , Automatic discovery and exploitation of promising subproblems for tabulation . in J Hooker (ed.) , Principles and Practice of Constraint Programming : 24th International Conference, CP 2018, Lille, France, August 27-31, 2018, Proceedings . Lecture Notes in Computer Science , vol. 11008 , Springer , pp. 3-12 , 24th International Conference on Principles and Practice of Constraint Programming (CP 2018) , Lille , France , 27/08/18 . https://doi.org/10.1007/978-3-319-98334-9_1conference
Principles and Practice of Constraint Programming
© 2018, Springer Nature Switzerland AG. This work has been made available online in accordance with the publisher’s policies. This is the author created accepted version manuscript following peer review and as such may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1007/978-3-319-98334-9_1
DescriptionFunding: EP/P015638/1 and EP/P026842/1. Dr Jefferson holds a Royal Society University Research Fellowship.
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