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Experimental studies of variable selection strategies based on constraint weights

机译:基于约束权的变量选择策略的实验研究

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Variable ordering heuristics that sample information before or during search in order to inform subsequent decisions have shown better performance and greater robustness than standard heuristics. One such strategy, the "weighted degree heuristic" is based on weighting constraints according to their involvement in failure during search. A more recent approach uses "random probing" with restarting to gain information less subject to sampling bias. To date, these approaches have not been carefully analysed experimentally. In the present work, several important findings are presented, including a better delineation of the class of events that is sampled, an analysis of the importance of informed choices at the beginning of search, and a demonstration that random probing identifies sources of global contention effectively even when these are not clearly demarcated. These experiments show how empirical analysis can clarify subtle issues in the analysis of heuristic procedures for difficult search problems. (c) 2008 Elsevier Inc. All rights reserved.
机译:在搜索之前或搜索过程中对信息进行采样以告知后续决策的可变排序启发法比标准启发法具有更好的性能和更强的鲁棒性。一种这样的策略,“加权度启发式”是基于它们在搜索过程中参与失败的加权约束。最近的一种方法是使用“随机探测”和重新启动来获得较少受采样偏差影响的信息。迄今为止,尚未对这些方法进行仔细的实验​​分析。在当前的工作中,提出了一些重要的发现,包括更好地描述了所采样事件的类别,在搜索开始时对明智选择的重要性进行了分析以及证明了随机探测可以有效地确定全球竞争的根源即使这些内容没有明确标出。这些实验表明,经验分析如何在针对困难搜索问题的启发式过程分析中澄清细微问题。 (c)2008 Elsevier Inc.保留所有权利。

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