• DocumentCode
    1637399
  • Title

    Co-evolutionary algorithm approach to a university timetable system

  • Author

    Chan, C.K. ; Gooi, H.B. ; Lim, M.H.

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
  • Volume
    2
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    1946
  • Lastpage
    1951
  • Abstract
    This paper describes an automated curriculum timetabling system based on a stochastic search methodology, namely a co-evolutionary algorithm. The application timetable is taken from the undergraduate courses of the School of Electrical and Electronic Engineering (EEE), Nanyang Technological University (NTU). A co-evolutionary algorithm approach is found to be well suited. Practical courses have duration greater than one hour. A schedule can be generated separately and its population, which consists of a set of practical schedules, is termed as the practical population. Lecture and tutorial schedules can also be generated separately. These are of one-hour duration and they are termed collectively as lecture/tutorial schedule. A set of lecture/tutorial schedules could be generated to form the lecture/tutorial population. These two populations use the same set of resources and have constraining effects upon one another. Since the placement of practical courses have a more constraining effect, the schedules in the practical population are first generated and are then used to guide the generation of the set of lecture/tutorial schedules. For every lecture/tutorial schedule generated, it is combined with its corresponding practical schedule to form a combined schedule. The average fitness of all the combined schedules is then computed and used as a measure of the fitness of the practical schedule that drives them. The practical population is then evolved progressively to obtain the best practical schedule. It is then used as a base configuration for the rest of the courses to populate and evolve. The resultant system compares favorably to the current manual system
  • Keywords
    educational administrative data processing; educational courses; engineering education; evolutionary computation; scheduling; search problems; stochastic processes; Nanyang Technological University; School of Electrical and Electronic Engineering; automated curriculum timetabling system; average fitness; co-evolutionary algorithm; lecture schedules; practical courses; practical population; practical schedule; stochastic search methodology; tutorial schedules; undergraduate courses; university timetable system; Databases; Education; Educational institutions; Evolutionary computation; Heuristic algorithms; Processor scheduling; Simulated annealing; Software systems; Space exploration; Stochastic systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    0-7803-7282-4
  • Type

    conf

  • DOI
    10.1109/CEC.2002.1004541
  • Filename
    1004541