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A multi-echelon inventory system with supplier selection and order allocation under stochastic demand

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  • Guo, Cong
  • Li, Xueping

Abstract

This paper investigates an integrated supplier selection and inventory control problems in supply chain management by developing a mathematical model for a multi-echelon system. In particular, a buyer firm that consists of one warehouse and N identical retailers procures a type of product from a group of potential suppliers, which may have different prices, ordering costs, lead times and have restriction on minimum and maximum total order size, to satisfy stochastic demand. A continuous review system that implements the order quantity, reorder point (Q, R) inventory policy is considered in the proposed model. The objective is to select suppliers and to determine the optimal inventory policy that coordinates stock levels between each echelon of the systems while properly allocating orders among selected suppliers to maximize the expected profit. The model is solved by decomposing the mixed integer nonlinear programming model into two sub-models. Numerical experiments are conducted to evaluate the model and some managerial insights are obtained with sensitivity analysis.

Suggested Citation

  • Guo, Cong & Li, Xueping, 2014. "A multi-echelon inventory system with supplier selection and order allocation under stochastic demand," International Journal of Production Economics, Elsevier, vol. 151(C), pages 37-47.
    • Handle: RePEc:eee:proeco:v:151:y:2014:i:c:p:37-47
    DOI: 10.1016/j.ijpe.2014.01.017
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    6. Dai, Zhuo & Aqlan, Faisal & Gao, Kuo, 2017. "Optimizing multi-echelon inventory with three types of demand in supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 107(C), pages 141-177.
    7. Chan, Chi Kin & Fang, Fei & Langevin, André, 2018. "Single-vendor multi-buyer supply chain coordination with stochastic demand," International Journal of Production Economics, Elsevier, vol. 206(C), pages 110-133.
    8. Ehsan Afshar Bakeshlou & Alireza Arshadi Khamseh & Mohammad Ali Goudarzian Asl & Javad Sadeghi & Mostafa Abbaszadeh, 2017. "Evaluating a green supplier selection problem using a hybrid MODM algorithm," Journal of Intelligent Manufacturing, Springer, vol. 28(4), pages 913-927, April.
    9. Govindan, Kannan, 2015. "The optimal replenishment policy for time-varying stochastic demand under vendor managed inventory," European Journal of Operational Research, Elsevier, vol. 242(2), pages 402-423.
    10. Noori-Daryan, Mahsa & Taleizadeh, Ata Allah & Jolai, Fariborz, 2019. "Analyzing pricing, promised delivery lead time, supplier-selection, and ordering decisions of a multi-national supply chain under uncertain environment," International Journal of Production Economics, Elsevier, vol. 209(C), pages 236-248.
    11. Sourour Aouadni & Jalel Euchi, 2022. "Using Integrated MMD-TOPSIS to Solve the Supplier Selection and Fair Order Allocation Problem: A Tunisian Case Study," Logistics, MDPI, vol. 6(1), pages 1-18, January.
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    13. Li, Xin & Ventura, José A. & Venegas, Bárbara B. & Kweon, Sang Jin & Hwang, Seong Wook, 2018. "An integrated acquisition policy for supplier selection and lot sizing considering total quantity discounts and a quality constraint," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 119(C), pages 19-40.
    14. Rajiv Kumar Sharma, 2022. "Examining interaction among supplier selection strategies in an outsourcing environment using ISM and fuzzy logic approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2175-2194, October.
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