• DocumentCode
    3004477
  • Title

    Adaptive Steady State Genetic Algorithm for scheduling university exams

  • Author

    Alsharafat, Wafa Slaibi ; AlSharafat, Mohammad Slaibi

  • Author_Institution
    Prince Hussein Bin Abdullah Coll. for IT, Al Al-Bayt Univ., Mafraq, Jordan
  • fYear
    2010
  • fDate
    11-12 June 2010
  • Firstpage
    70
  • Lastpage
    74
  • Abstract
    Scheduling exams timetable, first and second exams, for large number of courses within Al Al-Bayt university departments is a complex problem since it has to be solved by using traditional method, manually by hands. In addition, it takes several days of iterative work by taking feedback from student. We describe an effective solution to solve this problem by using different form of Genetic Algorithm; Steady State Genetic algorithm(SSGA), Enhanced Steady State Genetic Algorithm(ESSGA), and Simple Genetic Algorithm(SGA). After performing a set of tests using real student data from several departments, we found that the ESSGA gains better timetable than other methods.
  • Keywords
    adaptive scheduling; educational institutions; genetic algorithms; Al Al Bayt university department; adaptive steady state genetic algorithm; enhanced steady state genetic algorithm; exams timetable; simple genetic algorithm; university exam scheduling; Artificial intelligence; Biological cells; Fuzzy logic; Genetic algorithms; Genetic mutations; Information technology; Iterative algorithms; Processor scheduling; Scheduling algorithm; Steady-state; ESSGA; Genetic algorithms; SSGA; Scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking and Information Technology (ICNIT), 2010 International Conference on
  • Conference_Location
    Manila
  • Print_ISBN
    978-1-4244-7579-7
  • Electronic_ISBN
    978-1-4244-7578-0
  • Type

    conf

  • DOI
    10.1109/ICNIT.2010.5508555
  • Filename
    5508555