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

Salwani Abdullah, S. Ahmadi, E. K. Burke, M. Dror, B. McCollum

Research output: Contribution to journalArticle

40 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)1494-1502
Number of pages9
JournalJournal of the Operational Research Society
Volume58
Issue number11
DOIs
Publication statusPublished - Nov 2007
Externally publishedYes

Fingerprint

Timetabling
Methodology
Experiments
Benchmark
Graph
Partitioning
Experiment

Keywords

  • Examination timetabling
  • Improvement graph
  • Large neighbourhood
  • Tabu search

ASJC Scopus subject areas

  • Management of Technology and Innovation
  • Strategy and Management
  • Management Science and Operations Research

Cite this

A tabu-based large neighbourhood search methodology for the capacitated examination timetabling problem. / Abdullah, Salwani; Ahmadi, S.; Burke, E. K.; Dror, M.; McCollum, B.

In: Journal of the Operational Research Society, Vol. 58, No. 11, 11.2007, p. 1494-1502.

Research output: Contribution to journalArticle

@article{fd64044711594c1b9d22f4ef3778a465,
title = "A tabu-based large neighbourhood search methodology for the capacitated examination timetabling problem",
abstract = "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.",
keywords = "Examination timetabling, Improvement graph, Large neighbourhood, Tabu search",
author = "Salwani Abdullah and S. Ahmadi and Burke, {E. K.} and M. Dror and B. McCollum",
year = "2007",
month = "11",
doi = "10.1057/palgrave.jors.2602258",
language = "English",
volume = "58",
pages = "1494--1502",
journal = "Journal of the Operational Research Society",
issn = "0160-5682",
publisher = "Palgrave Macmillan Ltd.",
number = "11",

}

TY - JOUR

T1 - A tabu-based large neighbourhood search methodology for the capacitated examination timetabling problem

AU - Abdullah, Salwani

AU - Ahmadi, S.

AU - Burke, E. K.

AU - Dror, M.

AU - McCollum, B.

PY - 2007/11

Y1 - 2007/11

N2 - 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.

AB - 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.

KW - Examination timetabling

KW - Improvement graph

KW - Large neighbourhood

KW - Tabu search

UR - http://www.scopus.com/inward/record.url?scp=35348877211&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=35348877211&partnerID=8YFLogxK

U2 - 10.1057/palgrave.jors.2602258

DO - 10.1057/palgrave.jors.2602258

M3 - Article

AN - SCOPUS:35348877211

VL - 58

SP - 1494

EP - 1502

JO - Journal of the Operational Research Society

JF - Journal of the Operational Research Society

SN - 0160-5682

IS - 11

ER -