{"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":"29 1","pages":"118-125"},"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.