• DocumentCode
    2223243
  • Title

    A Machine Operation Lists based Memetic Algorithm for Job Shop Scheduling

  • Author

    Raeesi N, Mohammad R. ; Kobti, Ziad

  • Author_Institution
    Sch. of Comput. Sci., Univ. of Windsor, Windsor, ON, Canada
  • fYear
    2011
  • fDate
    5-8 June 2011
  • Firstpage
    2436
  • Lastpage
    2443
  • Abstract
    In this article, a new Memetic Algorithm (MA) has been proposed to solve Job Shop Scheduling Problems. The proposed MA is based on Machine Operation Lists (MOL), which is the exact sequence of operations for each machine. Machine Operation Lists representation is a modification of Preference List-Based representation. Linear Order Crossover (LOX) and Random operations are first considered as crossover and mutation operators for the proposed MA. Local Search heuristic (LS) of the proposed MA reconsiders all the operations of a job. It chooses a job and removes all of its operations and finally reassigns them again one by one in their sequencing order to improve the fitness value of the schedule. The proposed algorithm has been applied on the well-known benchmark of classical Job Shop Scheduling Problems (JSSP). Comparing it with the existing methods shows that the proposed MA and the proposed Genetic Algorithm (GA) without LS are effective in JSSP. Moreover, comparing the results of MA and GA shows that using LS not only improves the final results but also helps GA to converge to the final solution.
  • Keywords
    genetic algorithms; job shop scheduling; search problems; genetic algorithm; job shop scheduling problems; linear order crossover; local search heuristic; machine operation lists representation; memetic algorithm; preference list-based representation; random operations; Biological cells; Evolutionary computation; Genetic algorithms; Job shop scheduling; Memetics; Schedules; System recovery;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2011 IEEE Congress on
  • Conference_Location
    New Orleans, LA
  • ISSN
    Pending
  • Print_ISBN
    978-1-4244-7834-7
  • Type

    conf

  • DOI
    10.1109/CEC.2011.5949919
  • Filename
    5949919