Skip to main content

Optimising a presentation timetable using evolutionary algorithms

  • Conference paper
  • First Online:
Evolutionary Computing (AISB EC 1994)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 865))

Included in the following conference series:

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 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.

    Google Scholar 

  2. Michalewicz, Z., Genetic Algorithms + Data Structures = Evolution Programs, Springer-Verlag, London, 1992.

    Google Scholar 

  3. Davis, L., Handbook of Genetic Algorithms, van Nostrand Reinhold, London, 1992.

    Google Scholar 

  4. 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.

    Google Scholar 

  5. 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.

    Google Scholar 

  6. Goldberg, D. E. Genetic Algorithms in Search, Optimisation and Machine Learning, Addison Wesley, Reading, 1989.

    Google Scholar 

  7. 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.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Terence C. Fogarty

Rights and permissions

Reprints and permissions

Copyright information

© 1994 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

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

Download citation

  • DOI: https://doi.org/10.1007/3-540-58483-8_20

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58483-4

  • Online ISBN: 978-3-540-48999-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics