Improved CLP scheduling with task intervals
Proceedings of the eleventh international conference on Logic programming
Boosting combinatorial search through randomization
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
A Meta-heuristic for Subset Problems
PADL '01 Proceedings of the Third International Symposium on Practical Aspects of Declarative Languages
Low-knowledge algorithm control
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
An approach for dynamic split strategies in constraint solving
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
A hyperheuristic approach to select enumeration strategies in constraint programming
AIC'09 Proceedings of the 9th WSEAS international conference on Applied informatics and communications
Integration of constraint programming and metaheuristics
SARA'07 Proceedings of the 7th International conference on Abstraction, reformulation, and approximation
A hyperheuristic approach for dynamic enumeration strategy selection in constraint satisfaction
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation: new challenges on bioinspired applications - Volume Part II
A framework for autonomous search in the Eclipsesolver
IEA/AIE'11 Proceedings of the 24th international conference on Industrial engineering and other applications of applied intelligent systems conference on Modern approaches in applied intelligence - Volume Part I
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In Constraint Programming, enumeration strategies are crucial for resolution performances. The effect of strategies is generally unpredictable. In a previous work, we proposed to dynamically change strategies showing bad performances, and to use metabacktrack to restore better states when bad decisions were made. In this paper, we design and evaluate strategies to improve resolution performances of a set of problems. Experimental results show the effectiveness of our approach.