Optimizing school examination timetables with Integer Linear Programming

Scheduling school examinations is a complex and time-consuming process which often required school administrators to manually arrange numerous subjects across limited period or timeslots while avoiding student and resource conflicts. This study addresses the School Examination Timetabling Problem (SETP) by developing an optimization model using Integer Linear Programming (ILP) to create efficient and conflict free examination schedules. The study utilizes real data from a secondary school in Kelantan and applies the ILP model using Microsoft Excel’s Solver. The data consist of the timetabling of 28 examinations, each with a duration ranging from 1 to 2.5 hours, for three students’ classes over nine days. The study develops an ILP model with the objective function to maximize the effective allocation of examination hours while considering two hard constraints and one soft constraint. All examinations are scheduled exactly once and the limit number of examinations per day are considered as the hard constraints in this study. For a more convenient examination timetable, the soft constraint includes grouping certain examinations on the same day. Results demonstrate the applicability of ILP in examination timetabling problem especially in school and offers a practical solution that can be adapted by other academic institutions facing similar scheduling challenges.