考虑交通拥堵与碳排放影响的城市生鲜冷链物流路径优化的研究

Research on Urban Fresh Food Cold Chain Logistics Route Optimization Considering Traffic Congestion and Carbon Emission Impact

摘要: 针对目前电商生鲜产品配送环节中存在高成本、高碳排放等问题，本文基于传统生鲜冷链物流配送模型，在考虑碳排放的同时加入交通拥堵因素，构建以固定成本、运输成本、制冷成本、货损成本、碳排放成本和惩罚成本之和最小为目标的路径优化模型，并使用设计的人工鱼群灰狼混合优化算法来对模型进行求解。通过对算例中的原始配送路径和优化过后的优化路径的总成本比较，发现优化过后的总成本对比降低了约26.66%，从而验证了模型及算法的可行性。

Abstract: Addressing the issues of high costs and high carbon emissions in the current distribution of fresh products, along with the growing problem of urban traffic congestion, this study develops a path optimization model based on the traditional cold chain logistics distribution model. The model incorporates carbon emissions and traffic congestion factors, aiming to minimize the sum of fixed costs, transportation costs, refrigeration costs, product spoilage costs, carbon emission costs, and penalty costs. A designed hybrid optimization algorithm, the Artificial Fish Swarm and Grey Wolf Optimizer (AFS-GWO), is used to solve the model. By comparing the total costs of the original distribution path and the optimized path in a case study, it was found that the total cost after optimization decreased by approximately 26.66%, thus verifying the feasibility of the model and the algorithm.