• DocumentCode
    2689469
  • Title

    Inventory decisions for an assemble-to-order system with two ordering opportunities and multiple transportation modes

  • Author

    Fu, Ke

  • Author_Institution
    Lingnan Coll., Sun Yat-sen Univ., Guangzhou, China
  • fYear
    2009
  • fDate
    8-10 June 2009
  • Firstpage
    827
  • Lastpage
    830
  • Abstract
    We consider inventory decision for an assemble-to-order system with two ordering opportunities and a one-time uncertain demand. The manufacturer can place her first order of the components ahead of demand realization with relatively lower prices. The second emergent order can be placed with relatively higher prices after demand is realized in case of component shortages. There are a number of lead times for each component representing different transportation modes for the second order. The manufacturer has to choose the one that best balance the time and cost tradeoff. We formulate the problem as a stochastic programming problem. We further consider a simpler version with a single component and multiple lead times. We propose several structural properties and a decompose algorithm to solve the problem efficiently.
  • Keywords
    assembling; decision making; inventory management; lead time reduction; order processing; pricing; stochastic programming; transportation; assemble-to-order system; decompose algorithm; inventory decision; multiple lead time; multiple transportation mode; one-time uncertain demand; pricing; single component; stochastic programming; structural property; two ordering opportunity; Assembly systems; Costs; Electronics industry; Manufacturing; Pricing; Procurement; Stochastic processes; Sun; Transportation; Uncertainty; assemble-to-order system; component procurement lead times; demand uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Service Systems and Service Management, 2009. ICSSSM '09. 6th International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4244-3661-3
  • Electronic_ISBN
    978-1-4244-3662-0
  • Type

    conf

  • DOI
    10.1109/ICSSSM.2009.5174995
  • Filename
    5174995