A single-supplier, multi-buyer, multi-product VMI production-inventory system under partial backordering

Mokhtari, Hadi; Rezvan, Mohammad Taghi

doi:10.1007/s12351-017-0311-z

Cited by 18 publications

(11 citation statements)

References 41 publications

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“…Wu et al [40] studied the CS policy integrated supply chain model with delayed effect and advertising strategies. Mokhtari and Rezvan [27] have examined a VMI production model with partial back-ordering between the single supplier and multiple buyers. Ahmed et al [2] created a synergic inventory model with imperfect manufacturing in the context of a global supply chain.…”

Section: Vendor Managed Inventory and Consignment Stock Policymentioning

confidence: 99%

Optimization on dual-channel supply chain model with pricing decision and trapezoidal fuzzy demand under a controllable lead time

Karthick

Uthayakumar

2022

Complex Intell. Syst.

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This paper considers a dual-channel supply chain with one vendor and multiple buyers in which (1) one channel is an offline channel where standard products are produced and shipped to the buyers and (2) the second channel is an online channel with the flow of customized products between the vendor and the online buyers/consumers. The first channel follows a vendor managed inventory with consignment stock (VMI-CS) agreement between the vendor and buyers. The supply lead time between the vendor and the buyer is considered controllable, at a cost. Two models are analyzed: (1) in the first model, the standard and customized product’s demand rate is assumed to be price and lead time-sensitive, and (2) in the second model, the demands are uncertain or ambiguous and are treated as a trapezoidal fuzzy number. It is reasonably complex to obtain analytical solutions. Hence, two algorithms are proposed to obtain the numerical solution with the objective of maximizing total profit. Numerical examples, sensitivity analysis, and managerial insights are given to test the model. Finally, conclusions and directions for future research are provided.

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Section: Vendor Managed Inventory and Consignment Stock Policymentioning

confidence: 99%

Optimization on dual-channel supply chain model with pricing decision and trapezoidal fuzzy demand under a controllable lead time

Karthick

Uthayakumar

2022

Complex Intell. Syst.

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“…Nia, Far, and Niaki [8] considered an economic order quantity model under the green vendor-managed inventory (VMI) policy, which includes limited warehouse capacity, pallets, deliveries, and greenhouse-gas emissions. Mokhtari and Rezvan [12] applied VMI policy to solve a multi-item replenishment problem in GSCM. In their model, each retailer decides on a replenishment plan based on a limited amount of total GHG emissions.…”

Section: Literature Reviewmentioning

confidence: 99%

A Multi-Item Replenishment Problem with Carbon Cap-and-Trade under Uncertainty

2020

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Recently, as global warming has become a major issue, many companies have increased their efforts to control carbon emissions in green supply chain management (GSCM) activities. This paper deals with the multi-item replenishment problem in GSCM, from both economic and environmental perspectives. A single buyer orders multiple items from a single supplier, and simultaneously considers carbon cap-and-trade under limited storage capacity and limited budget. In this case we can apply a can-order policy, which is a well-known multi-item replenishment policy. Depending on the market characteristics, we develop two mixed-integer programming (MIP) models based on the can-order policy. The deterministic model considers a monopoly market in which a company fully knows the market information, such that both storage capacity and budget are already determined. In contrast, the fuzzy model considers a competitive or a new market, in which case both of those resources are considered as fuzzy numbers. We performed numerical experiments to validate and assess the efficiency of the developed models. The results of the experiments showed that the proposed can-order policy performed far better than the traditional can-order policy in GSCM. In addition, we verified that the fuzzy model can cope with uncertainties better than the deterministic model in terms of total expected costs.

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“…However, this paradigm requires the continuous and seamless communication between vendors and suppliers [3,4]. Moreover, the possibilities of the collaboration among suppliers and vendors in a collaborative environment can bring serious problems for VMI as the shared information among stakeholders can endanger the competitive advantages [5,6]. Also the complex interaction of supplies and vendors requires efficient tools to handle the financial transactions of stakeholders [7].…”

Section: Introductionmentioning

confidence: 99%

Using blockchain technology to extend the vendor managed inventory for sustainability

Ahmadi¹,

Khaturia²,

Sahraei³

et al. 2021

JCM

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Nowadays, Information Technology (IT) is changing the way traditional enterprise management concepts work. One of the most dominant IT achievements is the Blockchain Technology. This technology enables the distributed collaboration of stakeholders for their interactions while fulfilling the security and consensus rules among them. This paper has focused on the application of Blockchain technology to enhance one of traditional inventory management models. The Vendor Managed Inventory (VMI) has been considered one of the most efficient mechanisms for vendor inventory planning by the suppliers. While VMI has brought competitive advantages for many industries, however its centralized mechanism limits the collaboration of a pool of suppliers and vendors simultaneously. This paper has studied the recent research for VMI application in industries and also has investigated the applications of Blockchain technology for decentralized collaboration of stakeholders. Focusing on sustainability issue for total supply chain consisting suppliers and vendors, it has proposed a Blockchain based VMI conceptual model. The different capabilities of this model for enabling the collaboration of stakeholders while maintaining the competitive advantages and sustainability issues have been discussed.

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A single-supplier, multi-buyer, multi-product VMI production-inventory system under partial backordering

Cited by 18 publications

References 41 publications

Optimization on dual-channel supply chain model with pricing decision and trapezoidal fuzzy demand under a controllable lead time

Optimization on dual-channel supply chain model with pricing decision and trapezoidal fuzzy demand under a controllable lead time

A Multi-Item Replenishment Problem with Carbon Cap-and-Trade under Uncertainty

Using blockchain technology to extend the vendor managed inventory for sustainability

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