Research on a collaboration model of green closed-loop supply chains towards intelligent manufacturing

A closed-loop supply chain (CLSC) is a complete supply chain cycle that closes the flow of logistics from procurement to sales to reduce pollution and optimize returns. In this paper, we aim to address the problems of uncertain supply and demand, environmental pollution and the bullwhip effect in CLSCs. This paper constructs a green CLSC collaboration model with intelligent manufacturing and proposes a neural fictitious self-play (NFSP) algorithm based on reinforcement learning. A complete green CLSC collaboration model is constructed by modeling and analyzing indicators such as recycling prices and price sensitivity in the intelligent manufacturing supply chain, and dual-channel independent recycling and green dual-channel hybrid models are considered. Then, the ADMM algorithm is used in advance to solve the initial value of the mixed model, and the NFSP algorithm based on deep Q-learning is proposed to solve the green CLSC collaboration model. Studies have shown that the green CLSC collaboration model with intelligent manufacturing is an environmentally friendly solution that closely connects recyclers and retailers: it is an intelligent and efficient supply chain model.

Automated summary

This paper proposes a green closed-loop supply chain collaboration model based on intelligent manufacturing and addresses the issues of uncertain supply and demand, environmental pollution, and the bullwhip effect. The results show that this model can reduce pollution and optimize returns effectively.