基于客户满意度的低碳冷链多式联运路径优化

Multimodal Transport Path Optimization of Low-carbon Cold Chain Based on Customer Satisfaction

中文关键词: 多式联运  冷链物流  客户满意度  帝企鹅优化算法  路径优化

英文关键词: multimodal transport  cold chain logistics  customer satisfaction  Emperor Penguin Optimizer  path optimization

中文摘要:

      目的 实现生鲜产品的高效配送，尽可能提高客户满意度。方法 分析多式联运和冷链物流的特点，选择最优物流路径。在路径选择模型的建立中，结合客户对生鲜产品的质量及到货时间的满意程度，引入顾客满意度参数。同时响应国家“碳中和”政策的号召，在模型构建中考虑了低碳策略，以总成本最小、客户满意度最大为目标函数。以15个枢纽城市及公路、铁路、水路3种方式的冷链运输为例，将目前较新的帝企鹅算法与传统的启发式算法(遗传算法、粒子群算法)进行对比，并针对转运时间进行灵敏度分析。结果 最优联运路线对应的客户满意度为0.96，转运时间的增加导致总成本上升、客户满意度下降和最优路径发生变化。结论 帝企鹅算法在求解多式联运问题上具有较好的收敛速度和收敛精度，为多式联运承运人的决策提供了依据。转运时间的波动导致适应度函数发生变化，因此在兼顾客户满意度的前提下，选择合适的运输方式和路径，减少非必要的转运。

英文摘要:

      The work aims to achieve the efficient distribution of fresh products, so as to improve customer satisfaction as much as possible. The characteristics of multimodal transport and cold chain logistics were analyzed to select the optimal logistics path. In the establishment of the path selection model, customer satisfaction was introduced as a parameter based on customer satisfaction with the quality and arrival time of fresh products. At the same time, in response to the national "carbon neutrality" policy call, consideration was given to the model construction. A low-carbon policy was adopted, with the objective function of minimizing total cost and maximizing customer satisfaction. With the cold chain transport of 15 node cities and three transport modes of highway, railway and water as an example, the relatively new Emperor Penguin Optimizer was compared with the traditional classic heuristic algorithm (Genetic Algorithm, Particle Swarm Algorithm) and the sensitivity analysis was conducted on the parameter of transshipment time. The customer satisfaction corresponding to the optimal intermodal path was 0.96 and the increase in transshipment time would lead to an increase in total costs, a decrease in customer satisfaction, and a change in the optimal path. The Emperor Penguin Optimizer has good convergence speed and convergence accuracy in solving multimodal transport problems, which provides a basis for the decision-making of multimodal transport carriers. The fluctuation of transshipment time can lead to changes in the fitness function value, so it is crucial to choose the appropriate transport method and route while considering customer satisfaction, and reduce unnecessary transshipment.