Search Ordering Heuristics for Restarts-based Constraint Solving

摘要

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.