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An Evolutionary Approach to Constraint-Based Timetabling

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Advances in Artificial Intelligence. PRICAI 2000 Workshop Reader (PRICAI 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2112))

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Abstract

In this paper we present a timetabling system that uses a combination of a genetic algorithm and constraint satisfaction to maximally satisfy constraints of different strengths. A prototype system is presented for university examination timetabling. Experiments performed with different parameter settings for the genetic algorithm on some real world data are reported. The results obtained from the prototype are promising. An extension to the system is proposed to support incremental processing of user-supplied constraints. This is needed to support user-guided exploration of the solution space and to capture the incremental nature of human timetabling.

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Reference

  1. Colorni, A., Dorigo, M., Maniezzo, V.: Genetic Algorithms and Highly Constrained Problems: The Time-Table Case, in Schwefel, H.-P. and Manner, R (editors), Proceedings of the First International Conference on Parallel Problem Solving from Nature, Springer-Verlag, Lecture Notes in Computer Science (1991), Vol. 496.

    Google Scholar 

  2. Even, S., Itai, A., Shamir, A.: On the Complexity of Timetable and Multicommodity Flow Problems, SIAM Journal on Computing (1976), Vol. 5,No. 4, 691–703.

    Article  MATH  MathSciNet  Google Scholar 

  3. Garey, M.R., Johnson, D.S.: Computers and Intractability, W.H. Freeman and Company, San Francisco (1979).

    MATH  Google Scholar 

  4. Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs, Springer-Verlag, New York, (1992).

    MATH  Google Scholar 

  5. Mitchell, M., An Introduction to Genetic Algorithms, The MIT Press, Cambridge, Massachusetts, England, (1996).

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  6. Sharma, D., Chandra, N.: An Evolutionary Approach to Constraint-Based Timetabling, Proceedings of Constraint Processing Workshop, Australian Joint Artificial Intelligence Conference, Sydney, Australia (2000).

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  7. Whitley, D.: A Genetic Algorithm Tutorial, Colorado State University (1993).

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Mathematics & Computing Science, University of the South Pacific, Suva Fiji Islands

    Dharmendra Sharma & Nivlesh Chandra

Authors
  1. Dharmendra Sharma
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  2. Nivlesh Chandra
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Editor information

Editors and Affiliations

  1. CSIRO Mathematical and Information Sciences, 723 Swanston Street, Carlton, VIC 3053, Australia

    Ryszard Kowalczyk

  2. School of Computer Science and Information Technology, RMIT University, GPO Box 2476V, Melbourne, VIC 3001, Australia

    Seng Wai Loke

  3. Department of Computer and Information Science, Linköping University, 581 83, Linköping, Sweden

    Nancy E. Reed

  4. CSIRO Mathematical and Information Sciences, GPO Box 664, Canberra, ACT 2601, Australia

    Graham J. Williams

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© 2001 Springer-Verlag Berlin Heidelberg

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Sharma, D., Chandra, N. (2001). An Evolutionary Approach to Constraint-Based Timetabling. In: Kowalczyk, R., Loke, S.W., Reed, N.E., Williams, G.J. (eds) Advances in Artificial Intelligence. PRICAI 2000 Workshop Reader. PRICAI 2000. Lecture Notes in Computer Science(), vol 2112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45408-X_9

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  • DOI: https://doi.org/10.1007/3-540-45408-X_9

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42597-7

  • Online ISBN: 978-3-540-45408-3

  • eBook Packages: Springer Book Archive

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