Adaptive randomized descent algorithm for solving course timetabling problems

Anmar Abuhamdah, Masri Ayob

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

This work proposes an Adaptive Randomized Descent Algorithm (ARDA) for solving university course timetabling problems. The work aims is to produce an adaptive algorithm that can produce good quality timetable by assigning a set of courses (events) and students to a fixed number of timeslots and rooms subject to a set of constraints. ARDA delays the comparison between the quality of the candidate solution and the current solution. ARDA use a threshold value (that is calculated based on the average quality of some recently accepted solution) as an acceptance criterion. ARDA can adaptively manage to escape from local optima by intelligently changing the threshold value when the search is trap in local optima. This is done by estimating an appropriate threshold value based on the history of the search. Results tested on the Socha's benchmark datasets showed that, ARDA produces significantly good quality solutions when compared with late acceptance strategy in hill climbing, average late randomized descent within a reasonable time and comparable to other approaches tested on Socha's dataset.

Original languageEnglish
Pages (from-to)2516-2522
Number of pages7
JournalInternational Journal of Physical Sciences
Volume5
Issue number16
Publication statusPublished - Dec 2010

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descent
acceptability
thresholds
Adaptive algorithms
students
escape
rooms
Students
estimating
traps
histories

Keywords

  • Course timetabling problems
  • Late acceptance strategy hill climbing

ASJC Scopus subject areas

  • Physics and Astronomy(all)
  • Electronic, Optical and Magnetic Materials

Cite this

Adaptive randomized descent algorithm for solving course timetabling problems. / Abuhamdah, Anmar; Ayob, Masri.

In: International Journal of Physical Sciences, Vol. 5, No. 16, 12.2010, p. 2516-2522.

Research output: Contribution to journalArticle

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