Truck-Drone Hybrid Delivery Routing: A Mathematical Model and Micro-Evolutionary Algorithm

This study investigates a Feasibility-assured Mothership System (FAMS) model for truck-drone hybrid delivery. As a mothership system variant, it is considered to be able to bring benefits by using drones for low-cost short distance transportation. Besides, it depicts a scenario aligning closely with the current features of urban delivery services and adopts methods to increase drone utilization. Most importantly, the model addresses potential infeasibility resulting from assumptions in existing relevant literature. In this study, the FAMS is formulated as a mixed integer linear program (MILP) model and micro-evolutionary algorithm (MEA), a population-based algorithm that captures the structural characteristics of individuals in order to find high-quality solutions more efficiently, is proposed. The experimental results demonstrate the effectiveness of the algorithm. The performance of the two proposed crossover operators is analyzed as well. Furthermore, the cost efficiency of the FAMS under numerous situations including different truck-drone unit travel cost ratios and various combinations of drone technical features is confirmed.