• DocumentCode
    238620
  • Title

    AIRP: A heuristic algorithm for solving the unrelated parallel machine scheduling problem

  • Author

    Perdigao Cota, Luciano ; Nohra Haddad, Matheus ; Freitas Souza, Marcone Jamilson ; Nazario Coelho, Vitor

  • Author_Institution
    Dept. of Comput. Sci., Fed. Univ. of Ouro Preto, Ouro Preto, Brazil
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    1855
  • Lastpage
    1862
  • Abstract
    This paper deals with the Unrelated Parallel Machine Scheduling Problem with Setup Times (UPMSPST). The objective is to minimize the makespan. In order to solve it, we propose a heuristic algorithm, based on Iterated Local Search (ILS), Variable Neighborhood Descent (VND) and Path Relinking (PR). In this algorithm, named AIRP, an initial solution is constructed using the Adaptive Shortest Processing Time method. This solution is refined by the ILS, having an adaptation of the VND as local search method. The PR method is applied as a strategy of intensification and diversification during the search. The algorithm was tested in instances of the literature envolving up to 150 jobs and 20 machines. The computational experiments show that the proposed algorithm outperforms an algorithm from the literature, both in terms of quality and variability of the final solution. In addition, the algorithm established new best solutions for more than 80,5% of the test problems in average.
  • Keywords
    iterative methods; minimisation; scheduling; search problems; AIRP; ILS; PR; UPMSPST; VND; adaptive shortest processing time method; diversification strategy; heuristic algorithm; intensification strategy; iterated local search; local search method; makespan minimization; path relinking; solution quality; solution variability; unrelated parallel machine scheduling problem-with-setup times; variable neighborhood descent; Educational institutions; Heuristic algorithms; Job shop scheduling; Parallel machines; Processor scheduling; Schedules; Space exploration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2014 IEEE Congress on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-6626-4
  • Type

    conf

  • DOI
    10.1109/CEC.2014.6900245
  • Filename
    6900245