An informed genetic algorithm for the high school timetabling problem

Authors:
Rushil Raghavjee;Nelishia Pillay
Affiliations:
University of KwaZulu-Natal, KwaZulu-Natal, South Africa;University of KwaZulu-Natal, KwaZulu-Natal, SouthAfrica
Venue:
SAICSIT '10 Proceedings of the 2010 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists
Year:
2010

Citing 11
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Abstract

The high school timetabling problem differs drastically from one school to another and from country to country. The South African high school problem has not been researched. This paper presents a genetic algorithm (GA) to solve this problem for a particular high school. A two-phase approach is taken. The first phase uses a GA to evolve a timetable that meets the hard constraints of the problem. During the second phase a GA improves the quality of the solutions found during the first phase by reducing the soft constraint cost of the timetable. Domain knowledge, in the form of low-level construction heuristics, is used to guide the search during the first phase. The study experiments with the effect of using different low-level construction heuristics for this purpose. Each GA iteratively refines an initial population from one generation to the next by the processes of evaluation, selection and regeneration. The paper also reports on the performance of different mutation operators tested for regeneration.