• DocumentCode
    3123426
  • Title

    A fuzzy stochastic programming approach to solve the capacitated lot size problem under uncertainty

  • Author

    Sahebjamnia, Navid ; Torabi, S. Ali

  • Author_Institution
    Dept. of Ind. Eng., Univ. of Tehran, Tehran, Iran
  • fYear
    2011
  • fDate
    27-30 June 2011
  • Firstpage
    2327
  • Lastpage
    2334
  • Abstract
    This paper develops a fuzzy stochastic multi-objective linear programming (FSMOLP) model for a multi-level, multi item capacitated lot sizing problem (CLSP) in a multi assembly shop. The proposed model attempts to minimize the total cost consisting of total production variation cost, inventory cost, backlog cost and total setup cost while maximizing the resource utilization simultaneously. To cope with the uncertainty associated with the most of the input data, e.g., the demand and process-related parameters they are treated as fuzzy stochastic parameters with identical stochastic membership function during the planning horizon. To show the usefulness of the proposed solution method, a numerical example is first solved. Then, the usefulness of the proposed model is validated over a set of randomly generated test problems.
  • Keywords
    fuzzy set theory; linear programming; lot sizing; minimisation; stochastic programming; backlog cost; fuzzy stochastic multiobjective linear programming model; inventory cost; multiassembly shop; multiitem capacitated lot sizing problem; resource utilization maximization; stochastic membership function; total cost minimization; total production variation cost; total setup cost; Assembly; Lot sizing; Planning; Production planning; Stochastic processes; Uncertainty; Fuzzy Stochastic Multi-Objective Linear Programming; Multi assembly shop; Multi-level; multi-item capacitated lot sizing problem;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ), 2011 IEEE International Conference on
  • Conference_Location
    Taipei
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4244-7315-1
  • Electronic_ISBN
    1098-7584
  • Type

    conf

  • DOI
    10.1109/FUZZY.2011.6007653
  • Filename
    6007653