Affiliations: [a] School of Management, Hefei University of Technology, Hefei, Anhui, PR China | [b] Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, Anhui, PR China
Abstract: This paper focuses on addressing the “last 100 metres” home delivery in rural areas, using a cooperated delivery method of drones and truck. Considering the constraints of drone load, drone energy consumption and customer time window, a mixed integer linear programming model is established to minimize the delivery cost. Owing to the computational complexity of this problem, a double ant colony optimization with neighbourhood search is proposed. First, the raw data are sorted and encoded. Second, the ant colony optimization with search operators is used to solve drone routes and truck route. Finally, the local search algorithm with search operators is used to solve the connection point between the drones and truck to obtain the cooperated delivery routes. Extensive experiments are conducted on the instances randomly generated in the Solomon dataset, and results demonstrate the proposed algorithm effectively solves problems within reasonable runtimes. Sensitivity analysis is conducted on factors that may affect the delivery cost of the solution and provide insights about drones participating in the “last hundred metres” home delivery service.
