• DocumentCode
    3540228
  • Title

    Genetic algorithm and heuristic search for solving timetable problem case study: Universitas Pelita Harapan timetable

  • Author

    Lukas, Samuel ; Aribowo, Arnold ; Muchri, Milyandreana

  • Author_Institution
    Inf. Eng., Universitas Pelita Harapan, Tangerang, Indonesia
  • fYear
    2009
  • fDate
    4-6 Aug. 2009
  • Firstpage
    629
  • Lastpage
    633
  • Abstract
    Scheduling problem is a model of complicated problem. Too many things have to be considered in order to arrange a schedule, such as lecturer availabilities, a great number of classes and courses. To overcome this problem, genetic algorithm combined with heuristic search is proposed in this paper. This proposed method was tested several times, and the results show that despite small population, the best schedule still can be obtained.
  • Keywords
    educational administrative data processing; genetic algorithms; scheduling; Universitas Pelita Harapan timetable; genetic algorithm; heuristic search; lecturer availabilities; scheduling problem; timetable problem; Biological cells; Computer science; Education; Genetic algorithms; Genetic engineering; Genetic mutations; Informatics; Poles and towers; Processor scheduling; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applications of Digital Information and Web Technologies, 2009. ICADIWT '09. Second International Conference on the
  • Conference_Location
    London
  • Print_ISBN
    978-1-4244-4456-4
  • Electronic_ISBN
    978-1-4244-4457-1
  • Type

    conf

  • DOI
    10.1109/ICADIWT.2009.5273979
  • Filename
    5273979