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An Iterative local-search framework for solving constraint satisfaction problem
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DOI：10.1016/j.asoc.2007.12.006.png)
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摘要
En 中文
In this article, we introduce a new solving framework based on using alternatively two local-search algorithms to solve constraint satisfaction and optimization problems. The technique presented is based on the integration of local-search algorithm as a mechanism to diversify the search instead of using a build on diversification mechanisms. Thus, we avoid tuning the multiple parameters to escape from a local optimum. This technique improves the existing methods: it is generic especially when the given problem can be expressed as a constraint satisfaction problem. We present the way the local-search algorithm can be used to diversify the search in order to solve real examination timetabling problems. We describe how the local-search algorithm can be used to assist any other specific local-search algorithm to escape from local optimality. We showed that such framework is efficient on real benchmarks for timetabling problems. (C) 2007 Elsevier B.V. All rights reserved.
Keyword:
constraint satisfaction
local-search algorithm
tabu search
timetabling problem
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期刊
IF:
6.6
论文数:
1.4W
被引数:
4.8W
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