基于VNS-NSGA-Ⅱ的双目标绿色冷链运输路径优化

Dual-Objective Gr een Cold Chain Transportation Path Optimization Based on VNS-NSGA-Ⅱ

在绿色冷链物流高质量发展背景下,构建以成本最小化与顾客满意度最大化的双目标绿色冷链物流车辆运输优化模型具有重要的现实意义。文章探讨了变邻域搜索算法(VNS)与多目标遗传算法二代(NSGA-Ⅱ)结合的VNSNSGA-Ⅱ算法,通过组合策略优化双目标模型求解方法。最后,借助Solomon算例集和苏宁小店的实际数据进行算例对比、仿真求解与灵敏度分析,佐证了VNS-NSGA-Ⅱ算法更具灵活性和收敛性,可以提高搜索效率,趋近于全局最优性,有助于解决绿色冷链车辆路径优化问题,为绿色冷链运输企业的可持续发展提供了方法论。

Under the background of high-quality development of green cold chain logistics,it is of great practical significance to construct a dual-objective green cold chain logistics vehicle transportation optimization model which minimizes cost and maximizes customer satisfaction.In this paper,the VNS-NSGA-Ⅱalgorithm,which combines variable neighborhood search algorithm(VNS)and non-dominated sorting genetic algorithm II(NSGA-Ⅱ),is discussed to optimize the solution method of two-objective model by combining strategy.Finally,the comparison,simulation solution and sensitivity analysis of Solomon example set and the actual data of Suning Small Store are used to prove that the VNS-NSGA-Ⅱalgorithm is more flexible and convergent,which can improve the search efficiency and approach the global optimization,and is helpful to solve the routing optimization problem of green cold chain vehicles.It provides a methodology for the sustainable development of green cold chain transportation enterprises.