Optimization of Examination Centre Allocation Using Distance and Accessibility-Constrained Assignment Models

Abstract

The allocation of examination centres in large-scale competitive examinations is typically treated as an administrative process, often resulting in students being assigned to distant or inconvenient locations despite the availability of more suitable alternatives. Such assignments may increase travel burden, reduce preference satisfaction, and negatively affect the overall examination experience. This study investigates examination centre allocation as a constrained optimization problem and proposes a student-centric allocation framework based on Integer Linear Programming (ILP). The proposed model minimizes a composite hardship function incorporating travel distance, accessibility characteristics of examination centres, and student preference penalties while satisfying centre capacity constraints. To evaluate the framework, a synthetic examination environment consisting of 2,000 students and 20 examination centres was generated. A baseline allocation strategy was compared against the optimized allocation model using multiple performance metrics, including travel distance, hardship score, and preference satisfaction. Experimental results demonstrate substantial improvements under the optimized allocation. Average travel distance decreased from 464.05 to 59.01 units, representing an 87.3\% reduction, while average hardship decreased by approximately 86.6\%. First-preference satisfaction increased from 5.4\% to 43.1\%, and assignments outside student preference lists decreased significantly. Sensitivity analysis across multiple weighting configurations further showed that the framework remains robust under different policy priorities. The findings suggest that mathematical optimization can provide a practical and effective approach to examination centre allocation by simultaneously improving efficiency, accessibility, and student satisfaction while maintaining operational feasibility.