Robot-aided electric vehicle routing problem with lockers and prime customers prioritization
研究了整合电动汽车、配送机器人和储物柜的最后一公里配送问题，优先服务Prime会员，通过混合整数线性规划模型和元启发式算法求解，平均降低电动汽车路径成本52.94%和利用成本21.95%。
Satisfactory and fast customer service is one of the critical parts of last-mile delivery. Companies like Amazon prioritize Prime members with same-day delivery while offering lockers for customer convenience. Additionally, robot-aided Electric Vehicle (EV) delivery is recognized for its cost efficiency and fast service in densely populated areas. Integrating EVs, delivery robots, and lockers, and prioritizing Prime customers can improve efficiency and service responsiveness. This integrated approach offers home delivery by EVs and robots and self-pickup from lockers. Every customer is assigned a prize (profit), with a higher profit associated with the Prime membership. Each EV dispatches robots, with a “dispatch-wait-collect” tactic, to serve the customers, while some customers are allocated to the lockers. This study introduces the Robot-Aided Electric Vehicle Routing Problem with Lockers and Prime Customer Prioritization (REVRP-LPCP), which aims to determine the least-cost routes for EVs and robots, assign customers to lockers, and prioritize prime customers by serving them within a single-period planning horizon. The REVRP-LPCP is formulated using a mixed-integer linear programming model, improving the EV-only-based delivery system by 52.94% and 21.95% in EV route and utilization costs on average. A metaheuristic is introduced, incorporating problem-specific repair and improvement operators to efficiently address large instances of the problem, outperforming Gurobi in 36 large instances by an average of 2.79% in terms of solution quality. Also, our method has identified 44 new best solutions in the related benchmarks. A comprehensive sensitivity analysis is conducted, assessing various scenarios and providing managerial insights.