VMI for single-vendor multi-retailer supply chains under stochastic demand

Mateen, Arqum; Chatterjee, Ashis Kumar; Mitra, Subrata

doi:10.1016/j.cie.2014.10.028

Cited by 59 publications

(22 citation statements)

References 36 publications

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“…In that model, the vendor has one replenishment frequency for all of the retailers. Mateen et al (2015) analyzed a single vendor and multi-buyer inventory model and each buyer has an upper limit stock. Moreover, replenishment exceeding the limit generates a penalty cost in that model.…”

Section: Literature Reviewmentioning

confidence: 99%

“…We consider L i values to be exogenously specified parameters. Because we focus on the lateral transshipment under warehouse capacity constraints, we assume that each buyer has a certain product demand (consumption) rate which is a usual assumption in inventory literature (refer to Darwish and Odah, 2010;Hariga et al, 2014;Mateen et al, 2015). The order-quantity, reorder-point (Q, r) continuous review ordering policies are used at the buyers, each of whom has an inventory capacity.…”

Section: Model Descriptionmentioning

confidence: 99%

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Warehouse capacity sharing via transshipment for an integrated two-echelon supply chain

Feng

Moon

Ryu

2017

Transportation Research Part E: Logistics and Transportation Re

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a b s t r a c tWarehouse capacity constraint has been one obstacle to achieving the channel-wide optimal decision in inventory management. We studied an integrated inventory model consisting of a single vendor and multiple buyers with warehouse capacity sharing via transshipment. We proposed an optimal transshipment policy by developing nonlinear programming models and genetic algorithms as well as obtaining Karush-Kuhn-Tucker points. This inventory policy can significantly reduce the channel-wide cost and the performance is influenced by the consideration of fixed transshipment costs. Sensitivity analyses show that parameters have different impacts on the channel-wide cost and the performances of the algorithms.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Model Descriptionmentioning

confidence: 99%

Warehouse capacity sharing via transshipment for an integrated two-echelon supply chain

Feng

Moon

Ryu

2017

Transportation Research Part E: Logistics and Transportation Re

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“…Vendor managed inventory (VMI) is an improved sustainable inventory management system with cooperative strategy between vendors (manufacturers) and buyers (retailers) [1]. When the information flows from the retails to the manufacturers, the VMI system can reduce fluctuation amplification of the customers' demand.…”

Section: Introductionmentioning

confidence: 99%

Partially Smoothing and Gradient-Based Algorithm for Optimizing the VMI System with Competitive Retailers under Random Demands

Deng

Wan

2020

Mathematical Problems in Engineering

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Vendor managed inventory (VMI) is an improved sustainable inventory management system, but it is difficult to establish and solve an integrated Stackelberg game model under the complicated practical environment. In this paper, a bilevel programming model is proposed to formulate the VMI system by taking into account the uncertainty of demand, the competition among retailers, the cooperative advertising, the shortage and holding costs, and the practical constraints. For the established stochastic model being associated with continuously random demands, a deterministic mathematical program with complementarity constraints (MPCC) is first derived by expectation method and the first-order optimality conditions of the lower-level problem. en, with a partially smoothing technique, the MPCC is solved by transforming it into a series of standard smooth optimization subproblems. Finally, owing to complexity caused by evaluating the integrals with unknown decision variables in the objective function, an efficient algorithm is developed to solve the problem based on the gradient information of model. Sensitivity analysis has been employed to reveal a number of managerial implications from the constructed model and algorithm. (1) e participation rate depends on advertising expenditures from both the manufacturer and the retailer. ere exists an optimal threshold of participation rate for the manufacturer, which can be provided by the intersection point of the manufacturer and retailer's costprofit curves. (2) e manufacturer's advertising policy is less sensitive to uncertainty of demand than the change of the retailer's advertising policy. (3) e manufacturer in the VMI system should concern about the differences caused by symmetric or asymmetric retailers.

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“…Regarding the retailer's ordering times and quantities, the manufacturer decides about the frequency and the quantity of orders to the supplier to minimize the holding and ordering costs besides fulfilling retailer's demand without any shortage. So the manufacturer uses the integer-ratio policy (see also Guan & Zhao, 2010;Yu et al, 2009;Mateen et al, 2015;Hariga et al, 2013), in which the replenishment cycle of the manufacturer equals . In this inventory policy, the replenishment cycle of the manufacturer is an integer multiple ( ) of the common replenishment cycle ( ).…”

Section: Profit Function Of the Manufacturermentioning

confidence: 99%

“…They compared dominance of retailers and the manufacturer and showed that the retailer dominance, in general, results in higher supply chain efficiency and the highest overall efficiency is when the leader has the lowest market scale among other retailers. Mateen et al (2015) provided formulations for minimizing the expected total cost for the VMI when overstocking is penalized. They also studied four different VMI models in Palsule-Desai (2013) and formulated the costs for different aspects of inventory synchronization such as replenishment policy and batch size in product delivery and showed that the all VMI models have less cost than retailercontrolled system.…”

Section: Introductionmentioning

confidence: 99%

Pricing and inventory decisions in a vendor managed inventory system with revenue sharing contract

Haji¹,

Afzalabadi²,

Rasoul³

2018

10.5267/j.uscm

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In this paper, we design a revenue sharing contract to coordinate pricing and inventory control decisions in a serial supply chain consisting of one supplier, one manufacturer and one retailer. We assume that the retailer faces Poisson demand and his unsatisfied demands will be lost. The retailer applies one-for-one period policy in which he constantly places an order for one unit of product to the manufacturer in a predetermined time interval which results in a deterministic demand for the manufacturer. Solution procedures are developed to find the equilibrium in the Vendor Managed Inventory (VMI) program with a revenue sharing contract, in which no party is willing to deviate from for the sake of maximizing his own profit. Furthermore, we formulate the total profit of the system and obtain the optimal retail price and order cycle for the retailer and the inventory policy of manufacturer which maximizes the supply chain's total profit and at the end we will highlight the revenue sharing contract performance.

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VMI for single-vendor multi-retailer supply chains under stochastic demand

Cited by 59 publications

References 36 publications

Warehouse capacity sharing via transshipment for an integrated two-echelon supply chain

Warehouse capacity sharing via transshipment for an integrated two-echelon supply chain

Partially Smoothing and Gradient-Based Algorithm for Optimizing the VMI System with Competitive Retailers under Random Demands

Pricing and inventory decisions in a vendor managed inventory system with revenue sharing contract

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