• DocumentCode
    2969899
  • Title

    Combination of Genetic Algorithm and LP-metric to solve single machine bi-criteria scheduling problem

  • Author

    Aryanezhad, M.B. ; Jabbarzadeh, A. ; Zareei, A.

  • Author_Institution
    Dept. of Ind. Eng., Iran Univ. of Sci. & Technol., Tehran, Iran
  • fYear
    2009
  • fDate
    8-11 Dec. 2009
  • Firstpage
    1915
  • Lastpage
    1919
  • Abstract
    This paper addresses single machine bi-criteria scheduling problem with the aim of minimizing total weighted tardiness and weighted number of tardy jobs. While weighted number of tardy jobs measures the service quality provided to customers, total weighted tardiness quantify the magnitude of lateness of each job. Therefore, considering both objectives, simultaneously, will provide the highest customers satisfaction. Both objectives are known to be NP-hard, thus, Genetic Algorithm is hired to solve the problem. Since LP-metric method is a rigorous multi-objective technique for making a combined dimensionless objective, it is used to navigate the search direction of Genetic algorithm. In this way, we can reach to some of solutions that are compatible to decision maker´s opinion while overcoming the issue of problem complexity. Finally for testing the efficiency of the proposed approach, some test problems are solved.
  • Keywords
    computational complexity; customer satisfaction; genetic algorithms; single machine scheduling; LP metric; NP-hard problem; customers satisfaction; genetic algorithm; rigorous multi-objective technique; service quality; single machine bi-criteria scheduling problem; tardy job; total weighted tardiness minimization; Customer satisfaction; Genetic algorithms; Gold; Industrial engineering; Job shop scheduling; Navigation; Polynomials; Quality of service; Single machine scheduling; Testing; Genetic Algorithm; LP-metric;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management, 2009. IEEM 2009. IEEE International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-4869-2
  • Electronic_ISBN
    978-1-4244-4870-8
  • Type

    conf

  • DOI
    10.1109/IEEM.2009.5373207
  • Filename
    5373207