Activity-Based search for black-box constraint programming solvers

Authors:
Laurent Michel;Pascal Van Hentenryck
Affiliations:
University of Connecticut, Storrs, CT;Optimization Research Group, NICTA, Victoria Research Laboratory, The University of Melbourne, VIC, Australia
Venue:
CPAIOR'12 Proceedings of the 9th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Year:
2012

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Abstract

Robust search procedures are a central component in the design of black-box constraint-programming solvers. This paper proposes activity-based search which uses the activity of variables during propagation to guide the search. Activity-based search was compared experimentally to impact-based search and the wdeg heuristics but not to solution counting heuristics. Experimental results on a variety of benchmarks show that activity-based search is more robust than other heuristics and may produce significant improvements in performance.