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Peckish initialisation strategies for evolutionary timetabling

  • David Corne
  • Peter Ross
Genetic Algorithms
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1153)

Abstract

Some evolutionary algorithm (EA)/timetabling researchers find benefit from combining an EA with graph-colouring based greedy algorithms, while others opt for a simpler but faster method. We consider a combination of the two approaches, largely retaining the speed of the simpler method while adopting the greedy method to bootstrap the process. In this combination, the initial population is produced by a ‘peckish’ timetable construction algorithm, similar to a greedy algorithm, but less concerned with finding a best timeslot for an event at each step. We find peckish population initialisation more effective than either greedy or random initialisation on non-trivial problems. Peckish initialisation is shown to aid a simple hill-climbing approach in a similar way. Finally, we add to the growing observation that hill-climbing often outperforms an EA on timetabling problems, but that this effect is reversed on problems of particular overconstrainedness or difficulty.

Keywords

Greedy Algorithm Hard Constraint Initialisation Strategy Random Initialisation Timetabling Problem 
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 1996

Authors and Affiliations

  • David Corne
    • 1
  • Peter Ross
    • 2
  1. 1.Parallel Emergent & Distributed Architectures Laboratory, Department of Computer ScienceUniversity of ReadingReadingUK
  2. 2.Department of Artificial IntelligenceUniversity of EdinburghEdinburghUK

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