Investigating Ahuja-Orlin's large neighbourhood search approach for examination timetabling

Salwani Abdullah, Samad Ahmadi, Edmund K. Burke, Moshe Dror

Research output: Contribution to journalReview articlepeer-review

76 Scopus citations

Abstract

Since the 1960s, automated approaches to examination timetabling have been explored and a wide variety of approaches have been investigated and developed. In this paper we build upon a recently presented, sequential solution improvement technique which searches efficiently over a very large set of "adjacent" (neighbourhood) solutions. This solution search methodology, originally developed by Ahuja and Orlin, has been applied successfully in the past to a number of difficult combinatorial optimisation problems. It is based on an improvement graph representation of solution adjacency and identifies improvement moves by finding cycle exchange operations using a modified shortest path label-correcting algorithm. We have drawn upon Ahuja-Orlin's basic methodology to develop an effective automated exam timetabling technique. We have evaluated our approach against the latest methodologies in the literature on standard benchmark problems. We demonstrate that our approach produces some of the best known results on these problems.

Original languageEnglish (US)
Pages (from-to)351-372
Number of pages22
JournalOR Spectrum
Volume29
Issue number2
DOIs
StatePublished - Apr 2007
Externally publishedYes

Keywords

  • Examination timetabling
  • Improvement graph
  • Large neighbourhood

ASJC Scopus subject areas

  • Management Science and Operations Research

Fingerprint

Dive into the research topics of 'Investigating Ahuja-Orlin's large neighbourhood search approach for examination timetabling'. Together they form a unique fingerprint.

Cite this