Lecturers to courses structured assignment by zoning binary integer goal programming models featuring enhanced modified hungarian method (l-csaz bigpe-mhm models)

Assignment problem mainly concerns with optimally allocating and assigning a number of nn subjects with varying efficiencies to mm jobs such that the total cost is minimized. This study addresses the lecturer-to-course assignment problem, considering three aspects namely the lecturer preferences, competency levels and training needs. An enhanced Modified Hungarian Method) was employed to optimize lecturer allocation by identifying their Areas of Mathematics a zoning approach. Subsequently. three multiobjective Binary Integer Goal Programming models were proposed, which maximizes competency scores and minimizes training costs; which maximizes combined competency and preference scores and minimizing training costs; and which maximizes competency scores, maximizes preference and minimizes training costs of lecturers. Data were collected through online surveys and interviews with Mathematics lecturers and academic administrators at Universiti Teknologi MARA (UiTM) Shah Alam and Seremban campuses. The courses included are Mathematics courses offered at these two campuses. MATLAB’s intlinprog solver was used to solve the models. Results revealed that is best suited for the assignments at UiTM Shah Alam while performed best for UiTM Seremban. The models enable optimal assignments, identify lecturers’ upskilling needs and minimize training costs required for upskilling. Ultimately, the aim is to allow optimal assignment by AOM, identify upskilling, improve lecturers’ satisfaction and teaching quality, which contribute significantly to the university's academic excellence and institutional efficiency.