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Comparison Of Periodic-Review Inventory Control Policies In A Serial Supply Chain

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  • Nihan Kabadayı
  • Timur Keskintürk

Abstract

Supply chain management provides customers with the right product or service at a reasonable price, in the right place, at the right time, and with the best quality possible, thus increasing customer satisfaction. The inventory is held at the multiple sites in a supply chain. Effective and efficient management of inventory in the supply chain process has a significant impact on improving the ultimate customer service provided to the customer. Reducing inventory cost, which is a major part of total supply chain costs, will help provide products or services at a better price. This study aims to compare (R, S) and (R, S, Qmin) inventory control policies in a serial supply chain. We develop a simulation based genetic algorithm (GA) in order to find the optimal numerical "S" value that minimizes the total supply chain cost (TSCC) and compare our results between two methods.

Suggested Citation

  • Nihan Kabadayı & Timur Keskintürk, 2015. "Comparison Of Periodic-Review Inventory Control Policies In A Serial Supply Chain," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 3(2), pages 27-34, December.
    • Handle: RePEc:anm:alpnmr:v:3:y:2015:i:2:p:27-34
    DOI: http://dx.doi.org/10.17093/aj.2015.3.2.5000148311
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    References listed on IDEAS

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    1. Petrovic, Dobrila & Roy, Rajat & Petrovic, Radivoj, 1998. "Modelling and simulation of a supply chain in an uncertain environment," European Journal of Operational Research, Elsevier, vol. 109(2), pages 299-309, September.
    2. Kiesmüller, G.P. & de Kok, A.G. & Dabia, S., 2011. "Single item inventory control under periodic review and a minimum order quantity," International Journal of Production Economics, Elsevier, vol. 133(1), pages 280-285, September.
    3. Azadivar, Farhad & Tompkins, George, 1999. "Simulation optimization with qualitative variables and structural model changes: A genetic algorithm approach," European Journal of Operational Research, Elsevier, vol. 113(1), pages 169-182, February.
    4. Sven Axsäter & Kaj Rosling, 1993. "Notes: Installation vs. Echelon Stock Policies for Multilevel Inventory Control," Management Science, INFORMS, vol. 39(10), pages 1274-1280, October.
    5. Zhou, Bin & Zhao, Yao & Katehakis, Michael N., 2007. "Effective control policies for stochastic inventory systems with a minimum order quantity and linear costs," International Journal of Production Economics, Elsevier, vol. 106(2), pages 523-531, April.
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    More about this item

    Keywords

    Genetic Algorithm; Inventory Management; Simulation-based Genetic Algorithm; Supply Chain Management;
    All these keywords.

    JEL classification:

    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management

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