Journal of the Operational Research Society

, Volume 58, Issue 11, pp 1494–1502

A tabu-based large neighbourhood search methodology for the capacitated examination timetabling problem


    • University of Nottingham
  • S Ahmadi
    • De Montfort University
  • E K Burke
    • University of Nottingham
  • M Dror
    • University of Arizona
  • B McCollum
    • Queen's University Belfast
Case-Oriented Paper

DOI: 10.1057/palgrave.jors.2602258

Cite this article as:
Abdullah, S., Ahmadi, S., Burke, E. et al. J Oper Res Soc (2007) 58: 1494. doi:10.1057/palgrave.jors.2602258


Neighbourhood search algorithms are often the most effective known approaches for solving partitioning problems. In this paper, we consider the capacitated examination timetabling problem as a partitioning problem and present an examination timetabling methodology that is based upon the large neighbourhood search algorithm that was originally developed by Ahuja and Orlin. It is based on searching a very large neighbourhood of solutions using graph theoretical algorithms implemented on a so-called improvement graph. In this paper, we present a tabu-based large neighbourhood search, in which the improvement moves are kept in a tabu list for a certain number of iterations. We have drawn upon Ahuja–Orlin's methodology incorporated with tabu lists and have developed an effective examination timetabling solution scheme which we evaluated on capacitated problem benchmark data sets from the literature. The capacitated problem includes the consideration of room capacities and, as such, represents an issue that is of particular importance in real-world situations. We compare our approach against other methodologies that have appeared in the literature over recent years. Our computational experiments indicate that the approach we describe produces the best known results on a number of these benchmark problems.


examination timetablinglarge neighbourhoodimprovement graphtabu search

Copyright information

© Palgrave Macmillan Ltd 2007