Solving The Exam Scheduling Problems in Central Exams With Genetic Algorithms

TL;DR

This paper presents a two-stage genetic algorithm for exam scheduling that optimizes resource use, reduces costs, and improves efficiency in central examination organizations.

Contribution

It introduces a novel two-stage genetic algorithm approach for exam scheduling, focusing on resource optimization and minimizing costs in educational institutions.

Findings

The genetic algorithm successfully increased joint student sessions.

It minimized the number of buildings and classrooms used.

The approach proved effective in sample applications.

Abstract

It is the efficient use of resources expected from an exam scheduling application. There are various criteria for efficient use of resources and for all tests to be carried out at minimum cost in the shortest possible time. It is aimed that educational institutions with such criteria successfully carry out central examination organizations. In the study, a two-stage genetic algorithm was developed. In the first stage, the assignment of courses to sessions was carried out. In the second stage, the students who participated in the test session were assigned to examination rooms. Purposes of the study are increasing the number of joint students participating in sessions, using the minimum number of buildings in the same session, and reducing the number of supervisors using the minimum number of classrooms possible. In this study, a general purpose exam scheduling solution for educational institutions was presented. The developed system can be used in different central examinations to create originality. Given the results of the sample application, it is seen that the proposed genetic algorithm gives successful results.1