• DocumentCode
    2709625
  • Title

    Solving the Exam Timetabling Problem via a Multi-Objective Evolutionary Algorithm - A More General Approach

  • Author

    Cheong, C.Y. ; Tan, K.C. ; Veeravalli, B.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., National Univ. of Singapore
  • fYear
    2007
  • fDate
    1-5 April 2007
  • Firstpage
    165
  • Lastpage
    172
  • Abstract
    This paper studies a multi-objective instance of the university exam timetabling problem. On top of satisfying universal hard constraints such as seating capacity and no overlapping exams, the solution to this problem requires the minimization of the timetable length as well as the number of occurrences of students having to take exams in consecutive periods within the same day. While most existing approaches to the problem, as well as the more popular single-objective instance, require prior knowledge of the desired timetable length, the multi-objective evolutionary algorithm proposed in this paper is able to generate feasible solutions even without the information. The effectiveness of the proposed algorithm is benchmarked against a few recent and established optimization techniques and is found to perform well in comparison
  • Keywords
    education; evolutionary computation; minimisation; scheduling; minimization; multiobjective evolutionary algorithm; seating capacity; universal hard constraints; university exam timetabling problem; Computational intelligence; Costs; Evolutionary computation; Processor scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Scheduling, 2007. SCIS '07. IEEE Symposium on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    1-4244-0704-4
  • Type

    conf

  • DOI
    10.1109/SCIS.2007.367685
  • Filename
    4218612