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In this study, a vendor-managed inventory model is developed for a single-vendor multiple-retailer single-warehouse (SV-MR-SV) supply chain problem based on the economic order quantity in which demands are stochastic and follow a uniform probability distribution. In order to reduce holding costs and to help balanced on-hand inventory cost between the vendor and the retailers, it is assumed that all inventory is held at a central warehouse with the lowest cost among the parties. The capacity of the central warehouse is limited. The objective is to find the warehouse replenishment frequency, the vendor\'s replenishment frequency, the order points, and the order quantities of the retailers such that the total inventory cost of the integrated supply chain is minimized. The proposed model is a mixed integer nonlinear programming problem (MINLP); hence, a genetic algorithm (GA) is utilized to solve this NP-hard problem. The parameters of the GA are calibrated using the Taguchi method to find better solutions. Some numerical illustrations are solved at the end to demonstrate the applicability of the proposed methodology and to evaluate the performance of the solution method.

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This work investigates the effect of different inventory policies of a supply chain model using the system dynamics approach which belongs to the class of Vendor Managed Inventory (VMI), automatic pipeline, inventory and order based production control systems (VMI-APIOBPCS). This work helps management to investigate the effect of different policies such as adding the VMI system or third party logistic (TPL) on the whole cost of the supply chain. To this end, this work applies system dynamics in supply chain with two supplier and one retail channel which consists of VMI system. Moreover, this work studies the performance of the proposed model via three metrics: Bullwhip effect; satisfaction of the end-customer; the amount of the whole inventory of chain.

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Considered supply chain in this article consists of one vendor and multiple retailers where the vendor applies vendor managed inventory. Considering vendor as a leader and retailers as followers, Stackelberg game theory is applied for modeling and analyzing this system. A general mixed integer nonlinear model is developed which can optimizes the performance of the system under revenue sharing contract, wholesale price contract and centralized structure. Based on this model, we numerically analyzed the performance of revenue sharing contract in the considered supply chain and four states for revenue sharing contract are analyzed at the end. Moreover, in each state, performance of the system under revenue sharing contract is compared with the performance of the system under wholesale price contract and centralized structure.

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This paper, considers the supplier selection in three echelon supply chain with Vendor Managed Inventory (VMI) strategy under price dependent demand condition. As there is a lack of study on the supplier selection in VMI literature, this paper presents a VMI model in supply chain including multi supplier, one distributer and multi retailer that distributer selects suppliers. Two class models (traditional vs. VMI) are presented and we compare them to study the impact of VMI on supply chain and supplier selection. As the proposed model is a NP-hard problem, a meta-heuristics namely Harmony Search is employed to optimize the proposed models. We show that how the VMI system can effect on supplier selection and can change the set of selected suppliers. Finally the conclusion and further studies are presented