Applying metaheuristics to some timetabling problems

Abstract

This thesis is concerned with a modeling study of a class of timetabling problems that arise from an institution in Indonesia. The timetabling problem consists of two subproblems, the teacher assignment problem and the course scheduling problem. For the first subproblem, the objective is to balance the teachera??s work load, while for the second subproblem, the objective is to achieve an even distribution of course schedule. Three metaheuristics, simulated annealing, tabu search and genetic algorithm, are proposed for solving the two subproblems. The performance of the proposed algorithms is evaluated by two sets of real data and a set of randomly generated problem instances. The computational results show that the three proposed metaheuristics are able to generate good solutions to the problems.