• DocumentCode
    3573548
  • Title

    Research on CVaR model of supply chain with emergency ordering in selling season

  • Author

    Dongyan Chen ; Yongli Liu ; Xiuping Han

  • Author_Institution
    Sch. of Appl. Sci., Harbin Univ. Sci. & Technol., Harbin, China
  • fYear
    2014
  • Firstpage
    4970
  • Lastpage
    4975
  • Abstract
    The problem is studied for a class of retailer and supplier with risk aversion in a supply chain. By developing a CVaR model, the optimal decisions of the supply chain are presented, where we consider the management mode of emergency order and random demand of the market status. Firstly, by applying the sub-additivity of CVaR method, the CVaR models of the retailer, supplier and the entire supply chain are established based on negative return. Secondly, aiming at the different scope of the risk value of enterprise, the optimal pre-season ordering quantities of the retailer, supplier and the entire supply chain are discussed. To achieve the supply chain coordination, the retailer´s optimal pre-season ordering quantities is consistent with the entire supply chain´s, then, the supplier´s optimal emergency wholesale price in the selling season is presented. The sensitivity of the optimal emergency wholesale price in the selling season to the parameters is analyzed. Finally, the effectiveness and the change along with the parameters of the optimal decisions of supply chain are illustrated by a numerical example.
  • Keywords
    order processing; pricing; retailing; risk management; supply chain management; CVaR model; emergency ordering; market status; optimal decisions; optimal emergency wholesale price; retailing; risk aversion; selling season; supply chain; Automation; Educational institutions; Intelligent control; Numerical models; Reactive power; Sensitivity; Supply chains; CVaR models; emergency ordering in selling season; optimal decisions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation (WCICA), 2014 11th World Congress on
  • Type

    conf

  • DOI
    10.1109/WCICA.2014.7053557
  • Filename
    7053557