A Hybrid Heuristic Algorithm for Solving COVID-19’s Social Distancing at Universities Campus  

作　　者：Hassan Al-Tarawneh Khalid Al-Kaabneh Aysh Alhroob Hazem Migdady Issam Alhadid 

机构地区：[1]Department of Data sciences and Artificial Intelligence,Al-Ahlyyia Amman University,Amman,Jordan [2]Department of Software Engineering,Isra University,Amman,Jordan [3]Department of CSMIS,Oman college of management and technology,Muscat,Oman [4]Faculty of Information Technology and Systems,University of Jordan,Aqaba,Jordan

出　　处：《Computer Systems Science & Engineering》2022年第6期933-944,共12页计算机系统科学与工程（英文）

摘　　要：Social distancing during COVID-19 has become one of the most important measures in reducing the risks of the spread of the virus. Implementing thesemeasures at universities is crucial and directly related to the physical attendance ofthe populations of students, professors, employees, and other members on campus. This research proposes an automated scheduling approach that can help universities and schools comply with the social distancing regulations by providingassistance in avoiding huge assemblages of people. Furthermore, this paper proposes a novel course timetable-scheduling scheme based on four main constraints.First, a distance of two meters must be maintained between each student inside theclassroom. Second, no classrooms should contain more than 20% of their regularcapacity. Third, there would be no back-to-back classes. Lastly, no lectures shouldbe held simultaneously in adjacent classrooms. The proposed approach wasimplemented using a variable neighborhood search (VNS) approach with an adaptive neighborhood structure (AD-NS) to resolve the problem of scheduling coursetimetables at Al-Ahlyyia Amman University. However, the experimental resultsshow that the proposed techniques outperformed the standard VNS tested on university course timetabling benchmark dataset ITC2007-Track3. Meanwhile, theapproach was tested using datasets collected from the faculty of information technology at Al-Ahlyyia Amman University (Jordan). Where the results showed that,the proposed technique could help educational institutes to resume their regularoperations while complying with the social distancing guidelines.

关 键 词：COVID-19 social distance variable neighborhood search adaptive neighborhood structure university course timetable 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]