基于客户满意度的时变绿色车辆路径问题

Research on Distribution Route Optimization of Low-carbon Cold Chain in Time-varyingRoad Network Based on Customer Satisfaction

为改善冷链物流配送活动中高能耗高碳排放以及服务水平低等问题,文中提出一种令客户满意的时变绿色车辆路径问题。考虑到时变速度连续变化的特点,采用多项式函数刻画车辆行驶速度,在车辆载重和客户时间窗等约束下,构建总成本最小和客户满意度最大的多目标模型。通过引入大规模邻域搜索操作改进NSGA-II的局部搜索能力。实验结果表明,多目标优化模型可以很好地兼顾经济、环境和客户三方面要求,为决策者提供了强有力的决策支持。改进的NSGA-II在总成本方面平均降低了5.54%,在客户满意度方面平均提高了1.48%,表现出较好的求解性能。与静态路网下路径优化结果对比,本模型降低平均8.88%的经济成本和13.65%的碳排放量,提高平均18.11%的客户满意度。

At present,the cold chain logistics distribution activities show the problems of high energy consumption,high carbon emissions and low service quality.In order to solve these problems effectively,this paper proposes a time-dependend green vehicle routing problem on constumer satisfaction.Considering the characteristics of continuous change of time-varying velocity,a polynomial function is used to describe the driving speed.Under the constraints of vehicle load and customer time window,a multi-objective model with minimum total cost and maximum customer satisfaction is established.The local search capability of NSGA-II is improved by introducing large-scale neighborhood search operation.The experimental results show that the multi-objective optimization model can well take into consideration the requests of economy,environment and customers,and provide strong decision support for decision makers.After the improvement,the total cost of NSGA-II is reduced by 5.54%on average,and the customer satisfaction is increased by 1.48%on average,showing better solving performance.Compared with the route optimization results under the static road network,this model reduces the average cost by 8.88%and the average carbon emission by 13.65%,and improves the average customer satisfaction by 18.11%.