Search ordering heuristics for restarts-based constraint solving

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Abstract

Over the past decade impressive advances have been made in solving Constraint Satisfaction Problems by using of randomization and restarts. In this paper we propose a new class of variable and value ordering heuristics based on learning from nogoods without storing them. We show empirically that these heuristics dramatically improve the performance of restarts-based constraint solving.

Original languageEnglish
Title of host publicationProceedings of the Twentieth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2007
Pages182-183
Number of pages2
Publication statusPublished - 2007
Event20th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2007 - Key West, FL, United States
Duration: 7 May 20079 May 2007

Publication series

NameProceedings of the Twentieth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2007

Conference

Conference20th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2007
Country/TerritoryUnited States
CityKey West, FL
Period7/05/079/05/07

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