Neural Network for a Novel Disturbance Optimal Control Model for Inventory and Production Planning in a Four-Echelon Supply Chain with Reverse Logistic

In this paper, the strategy problems of pricing and store-assistance service investment are investigated for a supply chain with consumer return, where the considered supply chain under consignment contract consists of a single manufacturer and a single retailer. Firstly, we use differential equation to model the evolution of store-assistance service level and depict the effect of store-assistance service level on the return rate. By applying two-stage game, both optimal pricing and store-assistance service strategies are obtained based on the presented optimal control model. Subsequently, the committed dynamic consignment price contract is designed to coordinate and improve the performance of supply chain. Finally, a numerical example is provided to illustrate the impacts of the effectiveness of store-assistance service level and decay rate on the feasible region of corresponding contract.

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An Optimal Control Model of the Low-Carbon Supply Chain: Joint Emission Reduction, Pricing Strategies, and New Coordination Contract Design

IEEE Access ◽

10.1109/access.2020.3000482 ◽

2020 ◽

Vol 8 ◽

pp. 106273-106283

Author(s):

Hui Yu ◽

Shizhen Bai ◽

Dongyan Chen

Keyword(s):

Optimal Control ◽

Supply Chain ◽

Emission Reduction ◽

Contract Design ◽

Control Model ◽

Pricing Strategies ◽

Low Carbon ◽

Carbon Supply ◽

Coordination Contract

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Supply Chain Risk Prevention and Control Based on Fuzzy Influence Diagram and Discrete Hopfield Neural Network

Discrete Dynamics in Nature and Society ◽

10.1155/2021/1319932 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Xin Su ◽

Maohua Zhong

Keyword(s):

Neural Network ◽

Supply Chain ◽

Prevention And Control ◽

Hopfield Neural Network ◽

Control Model ◽

Risk Prevention ◽

Influence Diagram ◽

Occurrence Probability ◽

Supply Chain Risk ◽

And Control

Efficient and reasonable supply chain management helps enterprises improve their efficiency, reduce costs, shorten cash flow times, and reduce enterprise risks. Risk prevention and control is a safety symbol for supply chains. To explore different influence degrees of multirisk factors and multilinks on enterprises, we propose a supply chain risk prevention and control model based on a fuzzy influence diagram and Hopfield neural network. Using the model that both calculates the risk size and occurrence probability of the supply chain and allows identifying various risk prevention and control levels, the supply chain risk is evaluated both objectively and fairly. We analyzed the theoretical and practical properties of supply chain risk prevention and control models and used it in the H company to illustrate this model.

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