Abstract
A software solution based on a genetic algorithm (GA) optimization has been designed for creating a university class timetable. The prototype program has demonstrated the capability to define an acceptable schedule within a maximum stress, minimum resource environment. The constraints imposed in such a complex environment are resolved by the GA assisted by a dynamic penalty function and greedy algorithms using domain knowledge. These techniques create an intelligent genetic algorithm for solving discontinuous, complex, and highly epistatic optimization problems.
Dave Rich has worked in nuclear physics engineering and research for over twenty years, in which he currently works for TRW. This project represents a foray into artificial intelligence research, in which he works independently.
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Rich, D.C. (1996). A smart genetic algorithm for university timetabling. In: Burke, E., Ross, P. (eds) Practice and Theory of Automated Timetabling. PATAT 1995. Lecture Notes in Computer Science, vol 1153. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61794-9_59
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DOI: https://doi.org/10.1007/3-540-61794-9_59
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