• DocumentCode
    3073353
  • Title

    Genetic Algorithm Based Inventory Optimization Analysis in Supply Chain Management

  • Author

    Radhakrishnan, Pooja ; Prasad, V.M. ; Gopalan, M.R.

  • Author_Institution
    CSE Dept., PSG Inst. of Adv. studies, Coimbatore
  • fYear
    2009
  • fDate
    6-7 March 2009
  • Firstpage
    418
  • Lastpage
    422
  • Abstract
    Inventory management is one of the significant fields in supply chain management. Efficient and effective management of inventory throughout the supply chain significantly improves the ultimate service provided to the customer. Hence there is a necessity of determining the inventory to be held at different stages in a supply chain so that the total supply chain cost is minimized. Minimizing the total supply chain cost is meant for minimizing holding and shortage cost in the entire supply chain. This inspiration of minimizing Total Supply Chain Cost could be done only by optimizing the base stock level at each member of the supply chain. The dilemma occurring here is that the excess stock level and shortage level is very dynamic for every period. In this paper, we have developed a novel and efficient approach using Genetic Algorithm which clearly determines the most possible excess stock level and shortage level that is needed for inventory optimization in the supply chain so as to minimize the total supply chain cost.
  • Keywords
    genetic algorithms; inventory management; supply chain management; genetic algorithm; inventory optimization; shortage level; stock level; supply chain management; Algorithm design and analysis; Costs; Customer service; Genetic algorithms; Inventory management; Manufacturing; Production; Raw materials; Supply chain management; Supply chains; Genetic Algorithm; Inventory Optimization; Inventory control; Supply Chain Management; supply chain cost;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advance Computing Conference, 2009. IACC 2009. IEEE International
  • Conference_Location
    Patiala
  • Print_ISBN
    978-1-4244-2927-1
  • Electronic_ISBN
    978-1-4244-2928-8
  • Type

    conf

  • DOI
    10.1109/IADCC.2009.4809047
  • Filename
    4809047