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dc.contributor.authorBwowe, Benjamin
dc.date.accessioned2021-03-05T07:13:21Z
dc.date.available2021-03-05T07:13:21Z
dc.date.issued2020-12
dc.identifier.citationBwowe, B. (2020). Automated Scheduling and Room Allocation System Using Constraint Optimization. (Unpublished undergraduate dissertation) Makerere University. Kampala, Ugandaen_US
dc.identifier.urihttp://hdl.handle.net/20.500.12281/9290
dc.descriptionThis project seeks to utilize a Google OR Tools based algorithm to schedule lectures and allocate rooms at the Central Teaching Facilities.en_US
dc.description.abstractThe University student population has been increasing faster than the infrastructure it utilizes. This has brought about congestion in the available space which in turn budded poor learning conditions and hence a drop in the education quality. Two new Central Teaching Facilities were opened to curb the problem except, without a strict, optimal and organized scheduling system, were greatly underutilized and only developed new problems for both University and students. Classes were still overcrowded, general confusion on which room a lecture was taking place and monopoly on some rooms by “dominant” colleges, haunted the place. This created the need for an Automated Scheduling and Room Allocation algorithm to stamp the new problems and more. All university courses would be able to use the facilities, rooms would be allocated according to size and special requests for rooms would be handled professionally. At the core of the algorithm are variables and constraints. These were generated by interviewing custodians and observing students at the facilities for the required data. A web-based view and Raspberry Pi system were added to the system for interaction and display purposes respectively. The result was an optimal schedule generated by an algorithm using Google’s fast CP SAT Solver. This was backed by a light and quick web-based application made with Express.js,Node.js and Mongoose. A Raspberry Pi system using Vue.js to design the generated schedule displayed the timetable. The advantage of the Raspberry Pi was its low power consumption at acceptable rendering speeds.en_US
dc.description.sponsorshipThe ARMS Projecten_US
dc.language.isoenen_US
dc.subjectConstraint Optimization.en_US
dc.subjectAlgorithmen_US
dc.titleAutomated Scheduling and Room Allocation System Using Constraint Optimization.en_US
dc.typeThesisen_US


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