A proven optimal result for a benchmark instance of the uncapacitated examination timetabling problem

IF 1.4 4区 工程技术 Q4 ENGINEERING, MANUFACTURING Journal of Scheduling Pub Date : 2024-03-11 DOI:10.1007/s10951-024-00805-0
Angelos Dimitsas, Christos Gogos, Christos Valouxis, Vasileios Nastos, Panayiotis Alefragis
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Abstract

Examination timetabling is a problem well known to the scheduling community. Its simplest version, which is the uncapacitated examination timetabling problem, is easily described and comprehended. Nevertheless, proof of optimality is notoriously difficult even for moderate size problems. In this paper, we describe the effort that our team exercised in finally proving the optimality of the sta83 instance of Carter’s dataset. The problem was decomposed naturally in three parts and for each part a different approach managed to prove optimality of the currently best known solution. This work also presents optimal solutions to subproblems that exist in various public datasets problems and two best known solutions of such problems.

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无限制考试时间安排问题基准实例的最优结果证明
考试时间安排是时间安排界众所周知的一个问题。它的最简单版本,即无容限考试时间安排问题,很容易描述和理解。然而,即使对于中等规模的问题,最优性的证明也是出了名的困难。在本文中,我们将介绍我们团队为最终证明卡特数据集的 sta83 实例的最优性所付出的努力。该问题被自然分解为三个部分,每个部分都采用了不同的方法来证明当前已知最佳解决方案的最优性。这项工作还提出了各种公共数据集问题中存在的子问题的最优解,以及此类问题的两个已知最佳解。
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来源期刊
Journal of Scheduling
Journal of Scheduling 工程技术-工程:制造
CiteScore
3.80
自引率
10.00%
发文量
49
审稿时长
6-12 weeks
期刊介绍: The Journal of Scheduling provides a recognized global forum for the publication of all forms of scheduling research. First published in June 1998, Journal of Scheduling covers advances in scheduling research, such as the latest techniques, applications, theoretical issues and novel approaches to problems. The journal is of direct relevance to the areas of Computer Science, Discrete Mathematics, Operational Research, Engineering, Management, Artificial Intelligence, Construction, Distribution, Manufacturing, Transport, Aerospace and Retail and Service Industries. These disciplines face complex scheduling needs and all stand to gain from advances in scheduling technology and understanding.
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