Abstract
This paper describes a solution to the problem of scheduling student presentations which uses evolutionary algorithms. The solution uses a permutation based approach with each candidate schedule being coded for by a genotype containing six chromosomes. Five systems (chromosome representation and genetic operators) are described and their suitability assessed for this application. Three of the systems use direct representations of permutations, the other two use indirect representations. Experimental results with different fitness equations, operator rates and population and replacement strategies are also given. All the systems are shown to be good at solving the problem if the algorithm parameters are correct. The best parameters for each system are given along with those parameters that do particularly badly.
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Paechter B., Luchian H., Cumming A., and Petriuc M., “Two Solutions to the General Timetable Problem Using Evolutionary Methods”, to appear in The Proceedings of the IEEE Conference of Evolutionary Computation, 1994.
Michalewicz, Z., Genetic Algorithms + Data Structures = Evolution Programs, Springer-Verlag, London, 1992.
Davis, L., Handbook of Genetic Algorithms, van Nostrand Reinhold, London, 1992.
Oliver, I. M., Smith, D. J. and Holland, J. R. C. “A Study of Permutation Crossover Operators on the Travelling Salesman Problem”, in The Proceedings of the Second International Conference on Genetic Algorithms, Lawrence Erlbaum Associates, Hillsdale, New Jersey, 1987.
Goldberg, D. E. and Lingle, R., “Alleles, loci, and the Travelling Salesman Problem”, Proceedings of an International Conference on Genetic Algorithms and their Applications, 1985.
Goldberg, D. E. Genetic Algorithms in Search, Optimisation and Machine Learning, Addison Wesley, Reading, 1989.
Corne, D., Fang, H-L and Mellish C., “Solving the Modular Exam Scheduling Problem with Genetic Algorithms”, Proceedings of the Sixth International Conference of Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Edinburgh, 1993.
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© 1994 Springer-Verlag Berlin Heidelberg
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Paechter, B. (1994). Optimising a presentation timetable using evolutionary algorithms. In: Fogarty, T.C. (eds) Evolutionary Computing. AISB EC 1994. Lecture Notes in Computer Science, vol 865. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58483-8_20
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DOI: https://doi.org/10.1007/3-540-58483-8_20
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Online ISBN: 978-3-540-48999-3
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