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Chapter 15 An Adaptive Tie Breaking and Hybridisation Hyper-Heuristic for Exam Timetabling Problems

机译:第15章适用于考试时间表问题的自适应平局与混合超启发式

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摘要

Graph colouring heuristics have long been applied successfully to the exam timetabling problem. Despite the success of a few heuristic ordering criteria developed in the literature, the approaches lack the ability to handle the situations where ties occur. In this paper, we investigate the effectiveness of applying tie breakers to orderings used in graph colouring heuristics. We propose an approach to construct solutions for our problem after defining which heuristics to combine and the amount of each heuristic to be used in the orderings. Heuristic sequences are then adapted to help guide the search to find better quality solutions. We have tested the approach on the Toronto benchmark problems and are able to obtain results which are within the range of the best reported in the literature. In addition, to test the generality of our approach we introduced an exam timetabling instance generator and a new benchmark data set which has a similar format to the Toronto benchmark. The instances generated vary in size and conflict density. The publication of this problem data to the research community is aimed to provide researchers with a data set which covers a full range of conflict densities. Furthermore, it is possible using the instance generator to create random data sets with different characteristics to test the performance of approaches which rely on problem characteristics. We present the first results for the benchmark and the results obtained show that the approach is adaptive to all the problem instances that we address. We also encourage the use of the data set and generator to produce tailored instances and to investigate various methods on them.
机译:图形着色试探法长期以来一直成功地应用于考试时间表问题。尽管在文献中开发了一些启发式排序标准,这些方法仍缺乏处理发生联系的情况的能力。在本文中,我们研究了将平局决胜者应用于图着色启发法中使用的排序的有效性。在定义了要组合的启发式方法以及在排序中使用的每种启发式方法的数量之后,我们提出了一种构造问题解决方案的方法。然后,对启发式序列进行调整以帮助指导搜索以找到质量更好的解决方案。我们已经对多伦多基准问题进行了测试,并且能够获得文献报道中最好的结果。另外,为了测试我们方法的通用性,我们引入了考试时间表实例生成器和新的基准数据集,其格式与多伦多基准相似。生成的实例的大小和冲突密度各不相同。将此问题数据发布给研究团体的目的是为研究人员提供涵盖所有冲突密度的数据集。此外,可以使用实例生成器创建具有不同特征的随机数据集,以测试依赖于问题特征的方法的性能。我们提供了基准测试的第一个结果,获得的结果表明该方法适用于我们所解决的所有问题实例。我们还鼓励使用数据集和生成器来生成量身定制的实例并研究它们的各种方法。

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  • 来源
  • 会议地点 Cluj-Napoca(RO);Cluj-Napoca(RO)
  • 作者

    E.K. Burke; R. Qu; A. Soghier;

  • 作者单位

    Automated Scheduling, Optimisation and Planning (ASAP) Group School of CSIT,University of Nottingham, Nottingham, NG8 IBB, U.K.;

    Automated Scheduling, Optimisation and Planning (ASAP) Group School of CSIT,University of Nottingham, Nottingham, NG8 IBB, U.K.;

    Automated Scheduling, Optimisation and Planning (ASAP) Group School of CSIT,University of Nottingham, Nottingham, NG8 IBB, U.K.;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 人工智能理论;
  • 关键词

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