Abstract
Researchers are turning more and more to evolutionary algorithms (EAs) as a flexible and effective technique for addressing timetabling problems in their institutions. We present a class of specialised mutation operators for use in conjunction with the commonly employed penalty function based EA approach to timetabling which shows significant improvement in performance over a range of real and realistic problems. We also discuss the use of delta evaluation, an obvious and recommended technique which speeds up the implementation of the approach, and leads to a more pertinent measure of speed than the commonly used ‘number of evaluations’. A suite of realistically difficult benchmark timetabling problems is described and made available for use in comparative research.
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References
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© 1994 Springer-Verlag Berlin Heidelberg
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Ross, P., Corne, D., Fang, HL. (1994). Improving evolutionary timetabling with delta evaluation and directed mutation. In: Davidor, Y., Schwefel, HP., Männer, R. (eds) Parallel Problem Solving from Nature — PPSN III. PPSN 1994. Lecture Notes in Computer Science, vol 866. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58484-6_298
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DOI: https://doi.org/10.1007/3-540-58484-6_298
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