• DocumentCode
    1686106
  • Title

    A genetic programming approach to solve scheduling problems with parallel simulation

  • Author

    Beham, Andreas ; Winkler, Stephan ; Wagner, Stefan ; Affenzeller, Michael

  • Author_Institution
    Research Center Hagenberg, Upper Austrian University of Applied Sciences, Campus Hagenberg, Softwarepark 11, A-4232, Austria
  • fYear
    2008
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Scheduling and dispatching are two ways of solving production planning problems. In this work, based on preceding works, it is explained how these two approaches can be combined by the means of an automated rule generation procedure and simulation. Genetic programming is applied as the creator and optimizer of the rules. A simulator is used for the fitness evaluation and distributed over a number of machines. Some example results suggest that the approach could be successfully applied in the real world as the results are more than human competitive.
  • Keywords
    Assembly; Cost function; Dispatching; Genetic programming; Humans; Optimal scheduling; Production planning; Software engineering; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Processing, 2008. IPDPS 2008. IEEE International Symposium on
  • Conference_Location
    Miami, FL, USA
  • ISSN
    1530-2075
  • Print_ISBN
    978-1-4244-1693-6
  • Electronic_ISBN
    1530-2075
  • Type

    conf

  • DOI
    10.1109/IPDPS.2008.4536362
  • Filename
    4536362