Decision Optimization of Low-Carbon Dual-Channel Supply Chain of Auto Parts Based on Smart City Architecture - Zheng Liu; Bin Hu; Bangtong Huang; Lingling Lang; Hangxin Guo; Yuanjun Zhao (Complexity)
Affected by the Internet, computer, information technology, etc., building a smart city has become a key task of socialist construction work. The smart city has always regarded green and low-carbon development as one of the goals, and the carbon emissions of the auto parts industry cannot be ignored, so we should carry out energy conservation and emission reduction. With the rapid development of the domestic auto parts industry, the number of car ownership has increased dramatically, producing more and more CO2 and waste. Facing the pressure of resources, energy, and environment, the effective and circular operation of the auto parts supply chain under the low-carbon transformation is not only a great challenge, but also a development opportunity. Under the background of carbon emission, this paper establishes a decision-making optimization model of the low-carbon supply chain of auto parts based on carbon emission responsibility sharing and resource sharing. This paper analyzes the optimal decision-making behavior and interaction of suppliers, producers, physical retailers, online retailers, demand markets, and recyclers in the auto parts industry, constructs the economic and environmental objective functions of low-carbon supply chain management, applies variational inequality to analyze the optimal conditions of the whole low-carbon supply chain system, and finally carries out simulation calculation. The research shows that the upstream and downstream auto parts enterprises based on low-carbon competition and cooperation can effectively manage the carbon footprint of the whole supply chain through the sharing of responsibilities and resources among enterprises, so as to reduce the overall carbon emissions of the supply chain system.