An Automated Task Assignment System for University Lecturers
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Abstract
The aim of this research study was to develop an automated course assignment system for university lecturers using Mixed-Integer Linear Programming (MILP) with the objective of maximizing the planning score, which is derived from satisfaction scores and the total number of lecturers for all subjects. The study was conducted at the Faculty of Logistics, Burapha University, The study compared the model with the current approach over a period of two semesters. Three indicators were used to evaluate the performance: accuracy of allocation, teaching workload in credit allocation, and planning time. The results showed that the model outperformed the current approach in terms of accuracy of allocation and teaching workload in credit allocation. Specifically, it reduced workloads exceeding the minimum requirements by 2.92% and 14.78% per semester, respectively. Moreover, the model provided faster answers, with each iteration taking only 0.5-1 minute. The usability and satisfaction derived from using the model might not be explicitly clarified, but the model's results adhere to university regulations while also considering satisfaction as an important element within the objective function. Finally, this study successfully developed a model that effectively allocates tasks and reduces excessive workloads for university lecturers.
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