考虑碳排放的冷链物流配送中心选址及路径优化研究

Research on Optimization of Location and Route for Cold Chain Logistics Distribution Center Considering Carbon Emission

摘要: 近年来，为提高企业的服务质量，提高客户满意度，我国冷链物流公司已进行相应的改进，以提高企业的经济效益，但也加大了CO₂的排放。因此，本文针对碳排放的冷链物流配送中心选址及车辆路径的协调优化问题，提出一系列可行的解决办法，以促进企业的低碳转型。本文首先对协同优化问题进行了研究，对其能耗和影响因子进行了分析，并提出了相应的计算公式。以碳税为基础，将物流配送中心的建设与运营成本、车辆固定成本等因素综合考虑，构建了协同优化模型，提出了解决方案。在此基础上，利用计算机Matlab软件实现了两阶段遗传算法的求解。以芜湖市A公司为例，分别对有无碳排放成本的两种协同优化方法进行了研究。结果表明，提高碳税税率后，通过对两种方案比较，发现考虑碳排放成本的协同优化方案在总体费用和总排放量方面都是最小的，从而验证了该方案的可行性。

Abstract: In recent years, in order to improve the service quality of enterprises and improve customer satisfaction, China’s cold chain logistics companies have made corresponding improvements to improve the economic benefits of enterprises, but also increase CO₂ emissions. Therefore, this paper proposes a series of feasible solutions for the coordination and optimization of the location and transportation path of the cold chain logistics distribution center with carbon emissions, so as to promote the low-carbon transformation of enterprises. This paper initially investigates the collaborative optimization problem, analyzing its energy consumption and influencing factors, and proposes corresponding computational formulas. Based on carbon tax, a collaborative optimization model is constructed by comprehensively considering factors such as the construction and operational costs of logistics distribution centers, and the fixed costs of vehicles, along with their proposed solutions. Subsequently, a two-stage genetic algorithm is implemented using Matlab software for solution seeking. Taking Company A in Wuhu City as an example, the paper studies two collaborative optimization methods, one with and one without considering carbon emission costs. Results indicate that after increasing the carbon tax rate, comparison of the two schemes reveals that the collaborative optimization scheme considering carbon emission costs results in the lowest overall costs and total emissions, thereby verifying the feasibility of this approach.