Bashar A.AldeebMohammed Azmi Al-BetarNorita Md NorwawiKhalid A.AlissaMutasem K.AlsmadiAyman A.HazaymehMalek Alzaqebah2024-05-292024-05-2920212022-1-28Bashar A. Aldeeb, Mohammed Azmi Al-Betar, Norita Md Norwawi, Khalid A. Alissa, Mutasem K. Alsmadi, Ayman A. Hazaymeh, Malek Alzaqebah, Hybrid intelligent water Drops algorithm for examination timetabling problem, Journal of King Saud University - Computer and Information Sciences, 2021, , ISSN 1319-1578, https://doi.org/10.1016/j.jksuci.2021.06.016.1319-15781368-8810.1016/j.jksuci.2021.06.016https://www.sciencedirect.com/science/article/pii/S1319157821001634?via%3Dihubhttps://www.scopus.com/record/display.uri?eid=2-s2.0-85110100157&origin=resultslist&sort=plf-f&src=s&st1=Hybrid+Intelligent+Water+Drops+Algorithm+For+Examination+Timetabling+Problem&sid=f666f2eee814c566fe9e28d9f44277ed&sot=b&sdt=b&sl=91&s=TITLE-ABS-KEY%28Hybrid+Intelligent+Water+Drops+Algorithm+For+Examination+Timetabling+Problem%29&relpos=0&citeCnt=2&searchTerm=&featureToggles=FEATURE_NEW_DOC_DETAILS_EXPORT:1https://oarep.usim.edu.my/handle/123456789/10235The current study investigates the Intelligent Water Drops (IWD) metaheuristic algorithm to construct and produce good quality solutions for the university examination timetabling problem (UETP). The IWD is a population-based metaheuristic that simulates the dynamic of the river systems. The main motivations for investigating IWD algorithm for examination timetabling problem is the ability to explore the search space effectively. The main drawback of IWD algorithm is like other population-based algorithm in exploitation process where it is very efficient scanning several search space niches, but it is unable to drilling down in each niche to which it navigates. In this paper we propose a hybrid approach based on IWD and locale search algorithm to improve the exploitation of IWD algorithm. The experimental results demonstrated that the proposed algorithm (i.e., Hybrid IWD) obtained best results in three datasets when comparing with the best-known results performed by the swarm intelligent approaches. Finally, the proposed algorithm achieved one best results in comparison with the other metaheuristic approaches.enExamination Time table, Intelligent Water Drops algorithm, Metaheuristic, Locale search algorithm, OptimizationArticle11311