Constraint Programming (CP) is a powerful paradigm for solving Combinatorial Problems (generally issued from Decision Making). In CP, Enumeration Strategies are crucial for resolution performances. 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 work, we design and evaluate strategies to improve resolution performances of a set of problems.
|Title of host publication||Cutting-Edge Research Topics on Multiple Criteria Decision Making|
|Subtitle of host publication||20th International Conference, MCDM 2009, Chengdu/Jiuzhaigou, Proceedings|
|Number of pages||4|
|State||Published - 2009|
|Name||Communications in Computer and Information Science|