Multi-trucks-and-drones cooperative pickup and delivery problem

This study aims to propose a decision methodology on scheduling trucks and drones for truck-and-drone cooperative delivery and pickup system. A fleet contains multiple truck groups; each truck group is a truck with carrying multiple drones. The fleet serves a set of dispersed customers who have the requirements of pickup and delivery services as well as their due time for service. A mixed-integer linear programming (MILP) model is formulated in this study for routing the trucks and drones in the fleet so that each customer's pickup or delivery requirements could be served by either a truck or a drone before their required due time. For solving the MILP model efficiently, this study designs a novel hybrid algorithm by combining the column generation and the logic-based Benders decomposition. Based on the main frame of column generation algorithm, the hybrid algorithm uses logic-based Benders decomposition to solve the pricing problem, and dynamic programming to solve subproblems of logic-based Benders decomposition for the purpose of accelerating the whole algorithm's solving process. Numerical experiments are also conducted on the context of the Hangzhou city so as to validate the efficiency of the proposed hybrid algorithm. Some managerial implications are also derived on the basis of some sensitivity analysis. The proposed methodology, i.e., the MILP model and the novel hybrid algorithm, is potentially useful for platform operators who run the truck-and-drone based urban delivery systems.