Nash game model for optimizing market strategies, configuration of platform products in a Vendor Managed Inventory (VMI) supply chain for a product family

Yu, Yugang; Huang, George Q.

doi:10.1016/j.ejor.2010.02.039

Cited by 72 publications

(23 citation statements)

References 23 publications

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“…Taleizadeh et al (2013b) studied a joint single vendorbuyer supply chain problem with stochastic demand and fuzzy lead-time, which minimized the expected total cost by determining the reorder point and order quantity. Several authors discussed the benefits of VMI (Achabal et al, 2000;Borade et al, 2013;Claassen et al, 2008;Dong & Leung, 2009;Govindan et al, 2013;Razmi et al, 2009;Shen et al, 2013;Yu & Huang, 2010) and for a more detailed study about VMI benefits, refer to Govindan (2013).…”

Section: Introductionmentioning

confidence: 97%

The optimal replenishment policy for time-varying stochastic demand under vendor managed inventory

Govindan

2015

European Journal of Operational Research

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Section: Introductionmentioning

confidence: 97%

The optimal replenishment policy for time-varying stochastic demand under vendor managed inventory

Govindan

2015

European Journal of Operational Research

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“…An overview can be found in Nagarajan and Sošić (2008), which focuses on cooperative models including bargaining and coalition formation. Yu and Huang (2010) study a network with a supplier, multiple retailers and symmetric information, but assumes VMI supply. In this case, the retailers can decide about the retail prices and the advertising investments.…”

Section: Literature Reviewmentioning

confidence: 99%

A distributed coordination mechanism for supply networks with asymmetric information

Egri

Váncza

2013

European Journal of Operational Research

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The paper analyses the problem of coordination in supply networks of multiple retailers and a single supplier, where partners have asymmetric, private information of demand and costs. After stating generic requirements like distributedness, truthfulness, efficiency and budget balance, we use the apparatus of mechanism design to devise a coordination mechanism that guarantees the above properties in the network. The resulting protocol is a novel realisation of the widely used Vendor Managed Inventory (VMI) where the responsibility of planning is at the supplier. We prove that together with the required generic properties a fair sharing of risks and benefits cannot be guaranteed. We illustrate the general mechanism with a detailed discussion of a specialised version, assuming that inventory planning is done according to the newsvendor model, and explore the operation of this protocol through computational experiments.

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“…For instance, genetic algorithm has been used for finding the Stackelberg- [20] Nash equilibrium of a nonlinear, nonconvex, nondifferentiable multilevel programming model (Liu [21]). Complicated SNC problems involving the design of the hierarchical spanning tree network (Kim et al [22]) and that of a vendor managed inventory SNC network (Yu and Huang [23]) were also successfully solved by the genetic algorithm. In these papers, the efficiency of the genetic algorithm for solving complicated combinational problems, in terms of both speed and accuracy, has been demonstrated.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Optimization Algorithms: A Stochastic Closed-Loop Supply Chain Network Problem Involving Oligopolistic Competition for Multiproducts and Their Product Flow Routings

Zhou

Chan

Wong

et al. 2015

Mathematical Problems in Engineering

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Recently, the first oligopolistic competition model of the closed-loop supply chain network involving uncertain demand and return has been established. This model belongs to the context of oligopolistic firms that compete noncooperatively in a Cournot-Nash framework. In this paper, we modify the above model in two different directions. (i) For each returned product from demand market to firm in the reverse logistics, we calculate the percentage of its optimal product flows in each individual path connecting the demand market to the firm. This modification provides the optimal product flow routings for each product in the supply chain and increases the optimal profit of each firm at the Cournot-Nash equilibrium. (ii) Our model extends the method of finding the Cournot-Nash equilibrium involving smooth objective functions to problems involving nondifferentiable objective functions. This modification caters for more real-life applications as a lot of supply chain problems involve nonsmooth functions. Existence of the Cournot-Nash equilibrium is established without the assumption of differentiability of the given functions. Intelligent algorithms, such as the particle swarm optimization algorithm and the genetic algorithm, are applied to find the Cournot-Nash equilibrium for such nonsmooth problems. Numerical examples are solved to illustrate the efficiency of these algorithms.

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Nash game model for optimizing market strategies, configuration of platform products in a Vendor Managed Inventory (VMI) supply chain for a product family

Abstract: This paper discusses how a manufacturer and its retailers interact with each other to optimize their product marketing strategies, platform product configuration and inventory policies in a VMI

Cited by 72 publications

References 23 publications

The optimal replenishment policy for time-varying stochastic demand under vendor managed inventory

The optimal replenishment policy for time-varying stochastic demand under vendor managed inventory

A distributed coordination mechanism for supply networks with asymmetric information

Intelligent Optimization Algorithms: A Stochastic Closed-Loop Supply Chain Network Problem Involving Oligopolistic Competition for Multiproducts and Their Product Flow Routings

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