A two-echelon vehicle routing problem with mobile satellites and multiple commodities
研究了带多商品、多仓库和移动卫星的两级车辆路径问题，提出混合整数线性规划模型和AS-LNS元启发式算法，通过计算实验验证了模型和算法的有效性，并分析了关键参数对最后一公里配送策略的影响。
This paper extends the two-echelon vehicle routing problem (2E-VRP) by considering multiple commodities, multiple depots, and mobile satellites (i.e., the so-called 3M-2E-VRP). This problem also accommodates flexible last-mile delivery strategies by allowing direct deliveries via first-echelon vehicles (mobile satellites) and indirect deliveries through goods exchanges at meeting points, such as parking lots or customer locations. We first model the problem as a mixed-integer linear programming (MILP); and then develop an innovative metaheuristic algorithm to solve medium and large problem instances. The proposed metaheuristic (the so-called AS-LNS) combines an innovative Approximate Scheduling (AS) approach with Large Neighborhood Search (LNS). Computational experiments validate the 3M-2E-VRP formulation and demonstrate the effectiveness of the proposed AS-LNS algorithm. Key managerial insights are further presented through a comprehensive sensitivity analysis, wherein the impact of key parameters, such as fuel consumption and wage costs, and comparison of different problem variants, is investigated on last-mile delivery strategies. • 2E-VRP with mobile satellites an effective solution for last-mile delivery challenges. • Synchronized scheduling and efficient routing crucial with mobile satellites. • An approximate scheduling paired with a LNS to find efficient and effective solutions. • Reduced delivery costs and enhanced flexibility in delivery operations. • Practical insights for urban logistics optimization.