【摘要】 随着冷链物流发展，物流车的路径优化已逐渐显现在大众的视野中，但是运输成本与路径一直困扰着物流公司，针对此类情况，文中提出冷链物流车的路径优化。主要设计以下两个方面：通过建立冷链物流模型，从碳排放成本与车辆运输成本进行模型建立；通过改进的蚁群算法研究，引入最优最差蚁群算法与启发因子算法对其路径优化建立模型。通过传统蚁群算法的研究与改进后的蚁群算法可以缩短车辆行驶路径，改进后的蚁群算法可以提升收敛性，优化了车辆行驶路径。结果表明，基于改进的蚁群算法可以优化路线、降低运输成本，优于传统的蚁群算法路径优化，提高了公司运输效率。更多还原

【Abstract】 With the development of cold chain logistics, the route optimization of logistics vehicles has gradually appeared in the public’s vision. However, the transportation cost and route have been troubling logistics companies. In view of this, the route optimization of cold chain logistics vehicles is proposed. The following two aspects are mainly designed. By establishing a cold chain logistics model, the model is established by taking account of the carbon emission cost and vehicle transportation cost. By the research on the improved ant colony optimization(IACO) algorithm, the optimal and worst ACO algorithm and heuristic factor algorithm are introduced to establish the path optimization model. The traditional ACO algorithm and the IACO algorithm can shorten the vehicle driving path, and the ACO algorithm can improve the convergence and optimize the vehicle driving path. The results show that the IACO algorithm can optimize the route and reduce the transportation cost, which is better than that of the traditional ACO algorithm, so the improved algorithm can enhance the transportation efficiency of the company.更多还原