Scatter Search metaheuristic for Post-Enrolment Course Timetabling Problems: A Review

Ghaith M. Jaradat, M. Ayob, Zulkifli Ahmad
{"title":"Scatter Search metaheuristic for Post-Enrolment Course Timetabling Problems: A Review","authors":"Ghaith M. Jaradat, M. Ayob, Zulkifli Ahmad","doi":"10.4156/IJACT.VOL5.ISSUE11.13","DOIUrl":null,"url":null,"abstract":"In this study, the performance of Scatter Search (SS) meta-heuristic for the post-enrolment course timetabling problems reported in recent literature was reviewed. The aim is to address the strengths and limitations of the SS structure and mechanisms; to empower more studies; to investigate the capabilities of SS; and to enhance it for solving timetabling problems as a whole. The SS is almost similar to memetic algorithms. However, it has a memory of elite solutions (which considers both high quality and diverse solutions) and combines two or more solutions explicitly based on elitism. SS contains a mechanism to strike a balance between diversification and intensification of the search. SS has five major steps: initializing a diverse collection of solutions; general solutions improvement; memorizing elite solutions, solutions combination; and improving the selected solution. Based on the outcomes of SS (tested on post-enrolment course timetabling problems), which was reported in the literature, this study concluded that the impact of SS's strategies are significant for a successful SS search performance. These strategies are: memory update, solutions selection, diversification (i.e. similarity measurement), and solutions combination. Indeed, updating the memory and solutions combination, have the greatest impact on the performance of SS. Therefore, future studies regarding the design of these two strategies for solving timetabling problems is recommended to be more carefully designed.","PeriodicalId":90538,"journal":{"name":"International journal of advancements in computing technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of advancements in computing technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4156/IJACT.VOL5.ISSUE11.13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

In this study, the performance of Scatter Search (SS) meta-heuristic for the post-enrolment course timetabling problems reported in recent literature was reviewed. The aim is to address the strengths and limitations of the SS structure and mechanisms; to empower more studies; to investigate the capabilities of SS; and to enhance it for solving timetabling problems as a whole. The SS is almost similar to memetic algorithms. However, it has a memory of elite solutions (which considers both high quality and diverse solutions) and combines two or more solutions explicitly based on elitism. SS contains a mechanism to strike a balance between diversification and intensification of the search. SS has five major steps: initializing a diverse collection of solutions; general solutions improvement; memorizing elite solutions, solutions combination; and improving the selected solution. Based on the outcomes of SS (tested on post-enrolment course timetabling problems), which was reported in the literature, this study concluded that the impact of SS's strategies are significant for a successful SS search performance. These strategies are: memory update, solutions selection, diversification (i.e. similarity measurement), and solutions combination. Indeed, updating the memory and solutions combination, have the greatest impact on the performance of SS. Therefore, future studies regarding the design of these two strategies for solving timetabling problems is recommended to be more carefully designed.
散点搜索元启发式的入学后课程排课问题:综述
本研究回顾了近年来文献报道的散点搜索(SS)元启发式方法在入学后课程排课问题中的表现。其目的是解决党卫军结构和机制的优势和局限性;授权更多的研究;调查党卫军的能力;并从整体上加强对排课问题的解决。SS几乎类似于模因算法。然而,它有一个精英解决方案的记忆(考虑高质量和多样化的解决方案),并结合两种或更多的解决方案明确基于精英主义。SS包含一种在多样化和强化搜索之间取得平衡的机制。SS有五个主要步骤:初始化不同的解决方案集合;通用解决方案改进;记忆精英解,解组合;并改进所选的解决方案。基于文献中报道的SS(对入学后课程排课问题的测试)的结果,本研究得出结论,SS策略对成功的SS搜索绩效的影响是显著的。这些策略是:记忆更新、解决方案选择、多样化(即相似性测量)和解决方案组合。事实上,更新记忆和解决方案组合对学生排课成绩的影响最大。因此,未来关于这两种解决排课问题的策略设计的研究建议更仔细地设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信