A new neural network based construction heuristic for the examination timetabling problem

  • Authors:

  • P. H. Corr;B. McCollum;M. A. J. McGreevy;P. McMullan

  • Affiliations:

  • Queens University of Belfast, Northern Ireland;Queens University of Belfast, Northern Ireland;Queens University of Belfast, Northern Ireland;Queens University of Belfast, Northern Ireland

  • Venue:
  • PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
  • Year:
  • 2006

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Abstract

This paper examines the application of neural networks as a construction heuristic for the examination timetabling problem. Building on the heuristic ordering technique, where events are ordered by decreasing scheduling difficulty, the neural network allows a novel dynamic, multi-criteria approach to be developed. The difficulty of each event to be scheduled is assessed on several characteristics, removing the dependence of an ordering based on a single heuristic. Furthermore, this technique allows the ordering to be reviewed and modified as each event is scheduled; a necessary step since the timetable and constraints are altered as events are placed. Our approach uses a Kohonen self organising neural network and is shown to have wide applicability. Results are presented for a range of examination timetabling problems using standard benchmark datasets.