• DocumentCode
    1104001
  • Title

    A review of machine learning in scheduling

  • Author

    Aytug, Haldun ; Bhattacharyya, Siddhartha ; Koehler, Gary J. ; Snowdon, Jane L.

  • Author_Institution
    Dept. of Decision & Inf. Sci., Florida Univ., Gainesville, FL, USA
  • Volume
    41
  • Issue
    2
  • fYear
    1994
  • fDate
    5/1/1994 12:00:00 AM
  • Firstpage
    165
  • Lastpage
    171
  • Abstract
    This paper has two primary purposes: to motivate the need for machine learning in scheduling systems and to survey work on machine learning in scheduling. In order to motivate the need for machine learning in scheduling, we briefly motivate the need for systems employing artificial intelligence methods for scheduling. This leads to a need for incorporating adaptive methods-learning
  • Keywords
    learning (artificial intelligence); reviews; scheduling; adaptive methods; artificial intelligence methods; machine learning; scheduling; Artificial intelligence; Dynamic scheduling; Environmental management; Job shop scheduling; Machine learning; Manufacturing processes; Parallel processing; Processor scheduling; Production planning; Uncertainty;
  • fLanguage
    English
  • Journal_Title
    Engineering Management, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9391
  • Type

    jour

  • DOI
    10.1109/17.293383
  • Filename
    293383
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1104001