Optimal pricing and ordering in global supply chain management with constraints under random demand

Xin-bo, Zhang; Huang, Shuai; Wan, Zhong

doi:10.1016/j.apm.2016.06.054

Cited by 34 publications

(27 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Haji et al [34] assumed that the retailer's demand satisfies the Poisson distribution. Zhang et al [35,36] proposed two stochastic programming models to formulate the management problem of global supply chains in the case that product demands are continuous random variables. Wei et al [37] studied two different inventory management models with considering stochastic learning effect.…”

Section: Vmi System With Random Demandmentioning

confidence: 99%

“…Wei et al [37] studied two different inventory management models with considering stochastic learning effect. Owing to the complexity caused by evaluating the integrals with the unknown decision variables in the objective function, it was pointed out in [35] that the existing optimization algorithms, or the software packages such as MATLAB, CPLEX, and LINGO, cannot be directly used to solve the models. erefore, for the stochastic models with continuous random demands, it is valuable to develop an efficient algorithm to solve them based on the gradient information of the objective function and constraints.…”

Section: Vmi System With Random Demandmentioning

confidence: 99%

See 1 more Smart Citation

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

Deng

Wan

2020

Mathematical Problems in Engineering

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Vmi System With Random Demandmentioning

confidence: 99%

Section: Vmi System With Random Demandmentioning

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

Self Cite

View full text Add to dashboard Cite

show abstract

“…The studies are contributed to the literature by introducing different points such as price sensitive customer approach, return products, stock levels and also seasonal products. Although Elmaghraby and Keskinocak [12] provide a detailed review of dynamic pricing in different scenarios for different inventory situations and customer classification, the same area continues to be discussed in recent years [4,[13][14][15][16][17][18][19][20][21]. However, the discounting and replenishment decisions are not modeled in these studies, except Geoffrey et al In addition to these areas of works, some studies categorized the selling price time periods into terms; however, generally short term is preferred [22][23][24].…”

Section: Literature Reviewmentioning

confidence: 99%

“…The effects of some factors such as price elasticity and age-sensitivity of demand and age profile of initial inventory are modeled via deterministic mathematical modeling. The price discounts are differentiated via scenarios, and the effects on total revenue and waste are determined in detail [20,21,33,34]. The summaries of the reviewed articles are discussed in detail.…”

Section: Literature Reviewmentioning

confidence: 99%

A New Dynamic Pricing Model for the Effective Sustainability of Perishable Product Life Cycle

Tekin

Erol

2017

Sustainability

View full text Add to dashboard Cite

Perishable products run their life cycle in a short period of time due to the shortness of their shelf lives. Product efficiency falls when especially non-recyclable products are thrown away without being used. Furthermore, this kind of products that unnecessarily occupy shelves of supermarkets cause supermarkets to follow an insufficient stock management policy. Unconscious and unplanned use of our limited natural resources will deteriorate the product portfolio for future generations. Such unconscious production and consumption patterns will disrupt natural balance and damage sustainability of products. In addition to creating very high costs for producers, sellers and consumers alike, these unsold or stale products lead to environmental problems due to such pricing policies. In other words, although the products have to be thrown away without being sold is attributed by many managers to be attributable to the unplanned over-orders, the actual reason is something else. The real contributor of the problem is changing purchase attitudes of customers because of wrong pricing policies of wholesaler. In addition, limited resources are also consumed fast and in unnecessary amounts. The imbalance in respect to the sustainability of these products leads to increase in the production costs, procurement costs and failure to achieve balance among products to be kept in storage houses as some of the products occupy stocks unnecessarily. In the present study, a new pricing policy is developed for product stock whose shelf lives are about to expire and generally become waste to increase salability of these products in reference to fresher stocks of these products. The present study, which is designed to reduce the above-mentioned losses, will seek to minimize the cost of waste, maximize the profit earned by supermarkets from the product, maximize product utilization rates and ensure sustainability of products and stocks as well. Fulfillment of these objectives will increase productivity and enhance the significance of product efficiency and nature-friendly attitudes.

show abstract

“…To better focusing risk monitoring and risk management in the automotive industry supply chains on risks in order to enhance decision making in the upstream supply chain [17]. Taking into consideration the uncertainty of demand, cost of production, allocation of the transportation cost, shortage loss, tax rates and limitation of markdown rates [29]. Cost calculation for more accurate cost information than the traditional volume-based costing (VBC).…”

Section: Literature Reviewmentioning

confidence: 99%

Current Order and Inventory Models in Manufacturing Environments,A Review from 2008 to 2018

Momeni¹,

Tjprc²

2018

IJMPERD

View full text Add to dashboard Cite

Optimal pricing and ordering in global supply chain management with constraints under random demand

Cited by 34 publications

References 29 publications

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

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

A New Dynamic Pricing Model for the Effective Sustainability of Perishable Product Life Cycle

Current Order and Inventory Models in Manufacturing Environments,A Review from 2008 to 2018

Contact Info

Product

Resources

About