Activity-Based Search for Black-Box Constraint Programming Solvers

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...

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Bibliographic Details
Published inIntegration of AI and OR Techniques in Contraint Programming for Combinatorial Optimzation Problems Vol. 7298; pp. 228 - 243
Main Authors Michel, Laurent, Van Hentenryck, Pascal
Format Book Chapter
LanguageEnglish
Published Germany Springer Berlin / Heidelberg 2012
Springer Berlin Heidelberg
SeriesLecture Notes in Computer Science
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ISBN9783642298271
3642298273
ISSN0302-9743
1611-3349
DOI10.1007/978-3-642-29828-8_15

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Summary: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.
ISBN:9783642298271
3642298273
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-642-29828-8_15