Development of algorithms for timetabling problem: case study of the University of Dar es Salaam.

Timetabling problems consist of scheduling certain number of resources such as classes, teachers, courses and classrooms to a number of time slots on daily basis. The feasible combinations for these resources are the ones that avoid the conflicts between teachers, classes and rooms. Many combinatorial optimization problems arising in real life situations are large and hard (NP-hard). Timetabling problem is a class of NP-hard optimization problem whereby no optimal solution procedure is known to solve the problem in a reasonable time scale. However, some methods have been sought which efficiently produce a feasible solution in a reasonable time. However, these algorithms can not guarantee an optimal solution but give a good approximate solution. For a long time, initial course schedules at the University of Dar-Es-Salaam have been constructed manually depending on the experience of the timetabler, which has resulted into considerable wastage of time and resources. In this study, we have developed global heuristic algorithms for approximate solution to timetabling problem using two global heuristics, Tabu search and Simulated annealing. Both algorithms have been described and implemented using real data from the . The results were tested and comparative analysis done based on the solutions produced.