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Computational Study of Non-linear Great Deluge for University Course Timetabling

  • Joe Henry Obit
  • Dario Landa-Silva
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 299)

Abstract

The great deluge algorithm explores neighbouring solutions which are accepted if they are better than the best solution so far or if the detriment in quality is no larger than the current water level. In the original great deluge method, the water level decreases steadily in a linear fashion. In this paper,we conduct a computational study of a modified version of the great deluge algorithm in which the decay rate of the water level is non-linear. For this study, we apply the non-linear great deluge algorithm to difficult instances of the university course timetabling problem. The results presented here show that this algorithm performs very well compared to other methods proposed in the literature for this problem. More importantly, this paper aims to better understand the role of the non-linear decay rate on the behaviour of the non-linear great deluge approach.

Keywords

Water Level Decay Rate Problem Instance Penalty Cost Large Instance 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Joe Henry Obit
    • 1
  • Dario Landa-Silva
    • 1
  1. 1.ASAP Research Group, School of Computer ScienceUniversity of NottinghamUnited Kingdom

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