• DocumentCode
    2619701
  • Title

    A Comparison Of Inventory Optimization And Discrete-Event Simulation For Supply Chain Analysis

  • Author

    Murphy, Erin

  • Author_Institution
    3M Co., Saint Paul
  • fYear
    2007
  • fDate
    9-12 Dec. 2007
  • Firstpage
    2383
  • Lastpage
    2383
  • Abstract
    This 3M Company supply chain case study compares inventory optimization and discrete-event simulation methodologies, and presents an iterative approach between an optimization model and a discrete-event simulation model. We know that modeling provides value-added decision support for complex inventory management problems. The inventory optimization model assists in making the best decision in the tradeoff between cost and customer service, in specific system states. On the other hand, the discrete-event simulation model quantifies the impact, over time, of inventory management policies, thus illustrating feasibility and ranges of system performance. Is one approach "better" than the other? Could coupling the two models improve the solution? Each method has its own limitations and its own contribution to decision making, which are highlighted in this case study.
  • Keywords
    customer services; decision making; decision support systems; discrete event simulation; inventory management; iterative methods; supply chain management; 3M company supply chain analysis; complex inventory management; customer service; decision making; discrete-event simulation; inventory optimization model; iterative approach; value-added decision support; Cost function; Customer service; Decision making; Discrete event simulation; Inventory management; Iterative methods; Optimization methods; Supply chains; System performance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Simulation Conference, 2007 Winter
  • Conference_Location
    Washington, DC
  • Print_ISBN
    978-1-4244-1306-5
  • Electronic_ISBN
    978-1-4244-1306-5
  • Type

    conf

  • DOI
    10.1109/WSC.2007.4419898
  • Filename
    4419898