Modified Hungarian Method in Optimizing Preference Levels in Lecturer-To-Course Assignment

Abstract

Effective allocating lecturers to courses is vital in Higher Education Institutions, ensuring that faculty expertise and resources are used to their best advantage. Previous studies have often utilized the Hungarian method for this task, but the Modified Hungarian Method (MHM) has yet to be extensively explored. Moreover, incorporating lecturer preferences, which range across four distinct levels from having never taught the course to having participated in training for the course, into the assignment process has yet to be previously implemented. This paper introduces a mathematical programming method to enhance the formulation of the MHM model. The preference-based MHM (P-MHM) model incorporates lecturers’ course preferences, aiming to maximize the preferences obtained from lecturer-to-course assignments. We gathered preference data from Mathematics lecturers at UiTM Shah Alam via an online survey, which served as the input for the P-MHM model. This model was solved using MATLAB’s intlinprog function, producing an optimal assignment where lecturers are assigned to a maximum of three courses. The optimal results of the P-MHM model determine the most suitable course assignments for each lecturer based on their preference levels. The model seeks to enhance educational quality and improve overall academic outcomes by aligning lecturer capabilities with the courses offered.