• DocumentCode
    2896176
  • Title

    Three Genetic Algorithm Approaches to Parallel Machine Scheduling and Comparison with a Heuristic

  • Author

    Samur, Sumeyye ; Bulkan, Serol

  • Author_Institution
    Dept. of Ind. Eng., Marmara Univ., Istanbul, Turkey
  • fYear
    2010
  • fDate
    12-14 April 2010
  • Firstpage
    270
  • Lastpage
    274
  • Abstract
    In this research, we aim to assign jobs, having different processing and release times, to identical parallel machines in the most effective way. To do so; firstly we made a literature review to see what other researchers have done in this area. Secondly, we proposed three genetic algorithms each having different crossover methods. And at the end; we examined those three algorithms and also a heuristic which we already proposed and tested before. Based on the job size and machine size, some algorithms performed better results than others.
  • Keywords
    computational complexity; genetic algorithms; scheduling; crossover methods; genetic algorithm; heuristic comparison; parallel machine scheduling; Genetic algorithms; Heuristic algorithms; Industrial engineering; Information technology; Job shop scheduling; Parallel machines; Polynomials; Scheduling algorithm; Testing; Time factors; genetic algorithm; heuristic; makespan; parallel machine scheduling; release time;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology: New Generations (ITNG), 2010 Seventh International Conference on
  • Conference_Location
    Las Vegas, NV
  • Print_ISBN
    978-1-4244-6270-4
  • Type

    conf

  • DOI
    10.1109/ITNG.2010.184
  • Filename
    5501719