Faculty of Science and Technology

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Start date: 2004End date: 2006

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    Mathematical programming formulations for the examinations timetable problem: The case of the University of Dar es Salaam
    (African Journal of Science and Technology, 2004) Mushi, Allen R.
    Examinations Timetabling Problem (ETP) is the problem of assigning courses to be examined and candidates to time periods and examination rooms while satisfying a set of constraints. Every University has a different set of constraints and structure of examinations. Thus there is no general ETP model for all Universities around the world [1]. ETP is NP-Hard [2] and therefore no optimal algorithm is known for this problem which can solve a general problem within reasonable time. However, exact methods can be used to provide a benchmark for the heuristic methods. There is no general model for University Timetabling Problems because the problem feature differs from one University to another. In this paper we focus in the formulation of the ETP for the University of Dar as salaam. We formulate, test and compare three Integer Programming models. It is concluded that, although exact methods cannot give a solution to a real-size problem, these models give a good benchmark for testing the performance of other approaches. This paper also gives a direction for better exact models for the University of Dar es salaam’s ETP.
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    Tabu search heuristic for university course timetabling problem
    (African Journal of Science and Technology, 2006) Mushi, Allen R.
    In this study we have addressed the NP-Hard problem of academic course timetabling. This is the problem of assigning resources such as lecturers, rooms and courses to a fixed time period normally a week, while satisfying a number of problem-specific constraints. This paper describes a Tabu Search algorithm that creates timetables by heuristically minimizing penalties over infeasibilities. The algorithm is developed with special focus on the University of Dar-assalaam and compares the results with a previous manually generated timetable. It has been found that, the Tabu Search technique gives better results given a careful selection of parameters.