An adaptive genetic algorithm for solving the examination timetabling problem

Abstract

Examination timetabling is one of the most important administrative activities that take place in all academic institutions. In general, University Timetabling Automation is considered a complex and highly constrained problem, it is considered to be a combination of both time-based planning and optimization problem. Several approaches have been applied to solve this problem, such as simulated annealing, tabu search, graph coloring techniques, genetic algorithms. This thesis aims to design and implement exam timetable using genetic algorithms with adaptive parameter controls. The developed Automated Exam Timetable Tool (AETT) was designed especially for University of Malaya but can be used in other universities that have similar administration and management system. Based on the staff evaluation in the Examination Unit and other users at University Malaya, the new system produced better exam timetable comparing with the current system used at University Malaya. The Fitness Value of the best solution in the Exam Time Table System (ETTS) is 140 which is much better than the current system, therefore its considered relatively good solution comparing with the current system. In addition the new system is a fully automated system, while the current system is partly automated (20%). The new system developed using MATLAB 7.0, and can be used as a standalone application.