Route optimization of autonomous vehicles in the last-mile delivery operations

Abstract

This thesis investigates collaborative human-robot systems for delivery and pickup tasks. Chapter 2 proposes a novel Mixed Integer Linear Programming (MILP) model for couriers and Autonomous Mobile Lockers (AMLs) in delivery tasks, with a heuristic algorithm for large instances, demonstrating cost savings.

Chapter 3 introduces a delivery system using trucks and drones, presenting a Mixed Integer Programming (MIP) model and efficient heuristic algorithms for vehicle routing in large instances, highlighting optimal drone flight range and load capacity.

Chapter 4 presents an MIP model for e-grocery delivery with multiple time windows, combining truck and drone deliveries. A hybrid heuristic algorithm and Constraint Programming approach offer quick quality solutions, outperforming traditional platforms. Sensitivity analysis reveals benefits of customer choice in multiple time slots.

In summary, this thesis offers innovative models and algorithms for collaborative human-robot delivery systems, emphasizing efficiency, cost savings, and adaptability to diverse network setups and customer preferences.