Hybridizing meta-heuristics approaches for solving university course timetabling problems

Khalid Shaker, Salwani Abdullah, Arwa Alqudsi, Hamid Jalab

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

In this paper we have presented a combination of two meta-heuristics, namely great deluge and tabu search, for solving the university course timetabling problem. This problem occurs during the assignment of a set of courses to specific timeslots and rooms within a working week and subject to a variety of hard and soft constraints. Essentially a set of hard constraints must be satisfied in order to obtain a feasible solution and satisfying as many as of the soft constraints as possible. The algorithm is tested over two databases: eleven enrolment-based benchmark datasets (representing one large, five medium and five small problems) and curriculum-based datasets used and developed from the International Timetabling Competition, ITC2007 (UD2 problems). A new strategy has been introduced to control the application of a set of neighbourhood structures using the tabu search and great deluge. The results demonstrate that our approach is able to produce solutions that have lower penalties on all the small and medium problems in eleven enrolment-based datasets and can produce solutions with comparable results on the curriculum-based datasets (with lower penalties on several data instances) when compared against other techniques from the literature.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages374-384
Number of pages11
Volume8171 LNAI
DOIs
Publication statusPublished - 2013
Event8th International Conference on Rough Sets and Knowledge Technology, RSKT 2013 - Halifax, NS
Duration: 11 Oct 201314 Oct 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8171 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other8th International Conference on Rough Sets and Knowledge Technology, RSKT 2013
CityHalifax, NS
Period11/10/1314/10/13

Fingerprint

Timetabling
Metaheuristics
Tabu search
Curricula
Soft Constraints
Tabu Search
Penalty
Assignment
Universities
Benchmark
Demonstrate

Keywords

  • Course Timetabling
  • Great Deluge
  • Tabu Search

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Shaker, K., Abdullah, S., Alqudsi, A., & Jalab, H. (2013). Hybridizing meta-heuristics approaches for solving university course timetabling problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8171 LNAI, pp. 374-384). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8171 LNAI). https://doi.org/10.1007/978-3-642-41299-8_36

Hybridizing meta-heuristics approaches for solving university course timetabling problems. / Shaker, Khalid; Abdullah, Salwani; Alqudsi, Arwa; Jalab, Hamid.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8171 LNAI 2013. p. 374-384 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8171 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Shaker, K, Abdullah, S, Alqudsi, A & Jalab, H 2013, Hybridizing meta-heuristics approaches for solving university course timetabling problems. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 8171 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8171 LNAI, pp. 374-384, 8th International Conference on Rough Sets and Knowledge Technology, RSKT 2013, Halifax, NS, 11/10/13. https://doi.org/10.1007/978-3-642-41299-8_36
Shaker K, Abdullah S, Alqudsi A, Jalab H. Hybridizing meta-heuristics approaches for solving university course timetabling problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8171 LNAI. 2013. p. 374-384. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-41299-8_36
Shaker, Khalid ; Abdullah, Salwani ; Alqudsi, Arwa ; Jalab, Hamid. / Hybridizing meta-heuristics approaches for solving university course timetabling problems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8171 LNAI 2013. pp. 374-384 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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