On the use of multi neighbourhood structures within a Tabu-based memetic approach to university timetabling problems

Salwani Abdullah, Hamza Turabieh

Research output: Contribution to journalArticle

43 Citations (Scopus)

Abstract

Finding a good university timetabling system is not a simple task for a higher educational organisation. As a result, many approaches to generating sufficiently good solutions have been introduced. This is mainly due to the high complexity within the search landscape; moreover, each educational organisation has its own rules and specifications. In this paper, a Tabu-based memetic algorithm that hybridises a genetic algorithm with a Tabu Search algorithm is proposed as an improved algorithm for university timetabling problems. This algorithm is employed on a set of neighbourhood structures during the search process with the aim of gaining significant improvements in solution quality. The sequence of neighbourhood structures has been considered to understand its effect on the search space. Random, best and general sequences of neighbourhood structures have been evaluated in this work. The concept of a Tabu list is embedded to control the selection of neighbourhood structures that are not dependent on the problem domains during the optimisation process after the crossover and mutation operators are applied to the selected solutions from the population pool. The algorithm will penalise neighbourhood structures that are unable to generate better solutions. The proposed algorithm has been applied and evaluated against the latest methodologies in the literature with respect to standard benchmark problems. We demonstrate that the proposed algorithm produces some of the best known results when tested on ITC2007 competition datasets.

Original languageEnglish
Pages (from-to)146-168
Number of pages23
JournalInformation Sciences
Volume191
DOIs
Publication statusPublished - 15 May 2012

Fingerprint

Timetabling
Tabu Search Algorithm
Memetic Algorithm
Process Optimization
Search Space
Crossover
Tabu search
Mutation
Universities
Genetic Algorithm
Benchmark
Specification
Mathematical operators
Methodology
Dependent
Genetic algorithms
Operator
Specifications
Demonstrate

Keywords

  • Memetic algorithm
  • Multi neighbourhood
  • Tabu search
  • University timetabling

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications
  • Information Systems and Management

Cite this

On the use of multi neighbourhood structures within a Tabu-based memetic approach to university timetabling problems. / Abdullah, Salwani; Turabieh, Hamza.

In: Information Sciences, Vol. 191, 15.05.2012, p. 146-168.

Research output: Contribution to journalArticle

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