首页> 外文会议>Data Mining and Optimization, 2009. DMO '09 >Iterated two-stage multi-neighbourhood tabu search approach for examination timetabling problem
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Iterated two-stage multi-neighbourhood tabu search approach for examination timetabling problem

机译:迭代两阶段多邻域禁忌搜索方法用于考试时间表问题

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In this research, we introduce a set of multi-neighbourhood strategies of iterated two-stage tabu search, ITMTS, to solve examination timetabling problems. This work is based on the standard tabu search with some modifications that are derived from the neighbourhood structure. The neighbourhood structure has divided the neighbourhood search mechanism into two stages, vertical neighbourhood search and horizontal neighbourhood search. These search mechanisms will work alternately with different neighbourhood concentration and candidate evaluation. We test and evaluate ITMTS with the uncapacitated Carter benchmark datasets and standard Carter's proximity cost. Our results are comparable with other approaches that have been reported in the literature with regards to the Carter's benchmark dataset and have shown as a promising technique to be further enhanced.
机译:在这项研究中,我们介绍了一组迭代的两阶段禁忌搜索ITMTS的多邻域策略,以解决考试时间表问题。这项工作是基于标准禁忌搜索,并从邻域结构中进行了一些修改。邻域结构将邻域搜索机制分为垂直邻域搜索和水平邻域搜索两个阶段。这些搜索机制将与不同的邻里集中度和候选者评估交替工作。我们使用无能力的Carter基准数据集和标准Carter的接近成本来测试和评估ITMTS。我们的结果与文献中报告的有关卡特基准数据集的其他方法具有可比性,并且被证明是有希望得到进一步改进的技术。

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