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Compromise ratio with weighting functions in a Tabu Search multi-criteria approach to examination timetabling

机译:禁忌搜索多准则检查时间表中采用权重函数的折中率

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University examination scheduling is a difficult and heavily administrative task, particularly when the number of students and courses is high. Changes in educational paradigms, an increase in the number of students, the aggregation of schools, more flexible curricula, among others, are responsible for an increase in the difficulty of the problem. As a consequence, there is a continuous demand for new and more efficient approaches. Optimisation and Constraint Programming communities have devoted considerable attention to this difficult problem. Just the definition of a satisfactory, not to mention optimal, timetabling may be complex. In fact, to characterise a timetabling solution, a single criteria may not be enough, since what may be considered good for one group of students may be regarded inappropriate for other students, or teachers. In this paper, four criteria were used to characterise the spreading of the exams over the examination period. A set of constraints regarding the non-overlapping of exams with students in common was considered. A multi-objective optimisation program was used to handle the four criteria and a Tabu Search was implemented to find a good feasible solution for this problem. Two new features to increase the automation of the algorithm were proposed. First, it uses a Fuzzy Inference Ruled Based System to choose the tabu tenure of the elements in the tabu list. Secondly, a modified version of the Compromise Ratio (CR) is proposed, where the usual fixed weights are replaced by weighting functions to rank the neighbourhood solutions in each iteration. Sufficient conditions which guarantee the monotonicity of the weighting functions are presented. (C) 2016 Elsevier Ltd. All rights reserved.
机译:大学考试安排是一项艰巨而繁重的工作,尤其是在学生和课程数量很高的情况下。教育范式的变化,学生人数的增加,学校的聚集,课程的更灵活等等,都是导致问题难度增加的原因。结果,持续需要新的和更有效的方法。优化和约束编程社区已对该问题进行了相当多的关注。仅仅令人满意的时间表(更不用说最佳时间表)的定义可能很复杂。实际上,要描述时间表解决方案的特点,可能仅凭一个标准是不够的,因为可能认为对一组学生有利的标准不适合其他学生或教师。在本文中,使用四个标准来描述考试期间考试的分布。考虑了与普通学生不重叠考试的一系列限制。使用多目标优化程序来处理这四个条件,并且实施了禁忌搜索以找到针对此问题的良好可行解决方案。提出了两个增加算法自动化程度的新功能。首先,它使用基于模糊推理规则的系统来选择禁忌列表中元素的禁忌权。其次,提出了折衷率(CR)的修改版本,其中通常的固定权重由加权函数代替,以在每次迭代中对邻域解进行排序。给出了保证加权函数单调性的充分条件。 (C)2016 Elsevier Ltd.保留所有权利。

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