• DocumentCode
    2359193
  • Title

    Genetic Algorithm for the Single Machine Total Weighted Tardiness Problem

  • Author

    Ferrolho, Antonio ; Crisostomo, Manuel

  • Author_Institution
    Dept. of Electr. Eng., Superior Sch. of Technol. of Viseu
  • fYear
    2006
  • fDate
    18-20 Dec. 2006
  • Firstpage
    17
  • Lastpage
    22
  • Abstract
    Genetic algorithms can provide good solutions for scheduling problems. In this paper we present a genetic algorithm to solve the single machine total weighted tardiness problem, a scheduling problem which is known to be NP-hard. First, we present a new concept of genetic operators for scheduling problems. Then, we present a developed software tool, called HybFlexGA, to examine the performance of various crossover and mutation operators by computing simulations of scheduling problems. Finally, the best genetic operators obtained from our computational tests are applied in the HybFlexGA. The computational results obtained with 40, 50 and 100 jobs show the good performance and the efficiency of the developed HybFlexGA
  • Keywords
    computational complexity; genetic algorithms; scheduling; HybFlexGA; NP-hard problem; genetic algorithm; scheduling problem; single machine total weighted tardiness problem; Biological cells; Computational modeling; Dynamic programming; Genetic algorithms; Genetic mutations; Heuristic algorithms; Processor scheduling; Single machine scheduling; Software tools; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    E-Learning in Industrial Electronics, 2006 1ST IEEE International Conference on
  • Conference_Location
    Hammamet
  • Print_ISBN
    1-4244-0324-3
  • Electronic_ISBN
    1-4244-0324-3
  • Type

    conf

  • DOI
    10.1109/ICELIE.2006.347205
  • Filename
    4152761