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Evaluating and Improving Modern Variable and Revision Ordering Strategies in CSPs

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Języki publikacji
EN
Abstrakty
EN
A key factor that can dramatically reduce the search space during constraint solving is the criterion under which the variable to be instantiated next is selected. For this purpose numerous heuristics have been proposed. Some of the best of such heuristics exploit information about failures gathered throughout search and recorded in the form of constraint weights, while others measure the importance of variable assignments in reducing the search space. In this work we experimentally evaluate the most recent and powerful variable ordering heuristics, and new variants of them, over a wide range of benchmarks. Results demonstrate that heuristics based on failures are in general more efficient. Based on this, we then derive new revision ordering heuristics that exploit recorded failures to efficiently order the propagation list when arc consistency is maintained during search. Interestingly, in addition to reducing the number of constraint checks and list operations, these heuristics are also able to cut down the size of the explored search tree.
Wydawca
Rocznik
Strony
229--261
Opis fizyczny
Bibliogr. 42 poz., tab.
Twórcy
autor
  • Department of Information & Communication Systems Engineering, University of the Aegean, Karlovassi, Samos, 83200, Greece, abalafoutis@aegean.gr
Bibliografia
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  • [3] C. Bessière, A. Chmeiss, and L. Sais. Neighborhood-based variable ordering heuristics for the contraint satisfaction problem. In Proceedings of the 7th Conference on Principles and Practice of Constraint Programming (CP-2001), pages 61-75, 2001.
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  • [7] F. Boussemart, F. Hemery, and C. Lecoutre. Revision ordering heuristics for the Constraint Satisfaction Problem. In 10th International Conference on Principles and Practice of Constraint Programming (CP-2004), Workshop on Constraint Propagation and Implementation, Toronto, Canada, 2004.
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  • [39] R.J.Wallace and D. Grimes. Experimental studies of variable selection strategies based on constraint weights. Journal of Algorithms, 63(1-3):114-129, 2008.
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUS8-0010-0087
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