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Automatic timetabling in practice

  • R. C. Rankin
Genetic Algorithms
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1153)

Abstract

This paper describes the experience of using an automatic timetable generation system, based on a memetic algorithm, to produce working timetables for a large department that offers a range of undergraduate and postgraduate courses attended by some 500 students. The automatic algorithm is supported by a records system which permits manual data collection and editing, viewing and printing of timetables.

The paper outlines the operation of the department as far as it affects timetabling, the method developed to use the system and discusses the benefits and difficulties arising from its practical application.

The author is responsible for timetabling in the department.

Keywords

Student Group Memetic Algorithm Core Module Study Lesson Cost Criterion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    Paechter, B., Luchian, H., and Cumming, A., “An Evolutionary Approach to the General Timetable Problem”, The Scientific Annals of the “Al. I. Cuza” University of Iasi, special issue for the ROSYCS symposium 1993.Google Scholar
  2. [2]
    Paechter B., Luchian H., Cumming A., and Petriuc M., “Two Solutions to the General Timetable Problem Using Evolutionary Methods”, The Proceedings of the IEEE Conference of Evolutionary Computation, 1994.Google Scholar
  3. [3]
    Paechter, B., Cumming, A., Luchian, H., “The Use of Local Search Suggestion Lists for Improving the Solution of Timetable Problems with Evolutionary Algorithms.”, AISB Workshop in Evolutionary Computing, Sheffield, April 1995.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • R. C. Rankin
    • 1
  1. 1.Department of Computer StudiesNapier UniversityEdinburghScotland

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