Abstract
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.
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Monfroy, E., Castro, C., Crawford, B. (2006). Adaptive Enumeration Strategies and Metabacktracks for Constraint Solving. In: Yakhno, T., Neuhold, E.J. (eds) Advances in Information Systems. ADVIS 2006. Lecture Notes in Computer Science, vol 4243. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11890393_37
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DOI: https://doi.org/10.1007/11890393_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46291-0
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