<![CDATA[Course scheduling is a complex combinatorial optimization problem frequently constrained by limited physical resources and time availability. This study formulates a mathematical model to optimize the Even Semester course schedule at the Computer Science Study Program, HKBP Nommensen Pematangsiantar University, which operates under critical infrastructure constraints: five regular classrooms and one computer laboratory. The Weighted Goal Programming (WGP) method with a binary Mixed Integer Linear Programming (MILP) approach was implemented using Python software. The model integrates hard constraints to guarantee a conflict-free schedule for both rooms and lecturers, and accommodates soft constraints through hierarchical priority weighting. Priority goals include optimizing laboratory allocation for practicum courses, equalizing lecturers' teaching workloads to prevent burnout, and minimizing late-evening class sessions. Computational results confirm that the model achieved convergence to a Global Optimal Solution with an objective function value of 19. The WGP model successfully eliminated all scheduling conflicts (zero conflict) and compressed the physical facility requirement from 13 rooms in the manual schedule to only five regular classrooms and one computer laboratory. Furthermore, the proportion of evening classes was significantly reduced, resulting in a more efficient, equitable, and operationally applicable course schedule.]]>
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