Route optimization of autonomous vehicles in the last-mile delivery operations
Access status:
Open Access
Type
ThesisThesis type
Doctor of PhilosophyAuthor/s
Ensafian, HamidrezaAbstract
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, ...
See moreThis 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.
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See moreThis 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.
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Date
2023Licence
Copyright All Rights ReservedRights statement
The author retains copyright of this thesis. It may only be used for the purposes of research and study. It must not be used for any other purposes and may not be transmitted or shared with others without prior permission.Faculty/School
The University of Sydney Business School, Institute of Transport and Logistics Studies (ITLS)Awarding institution
The University of SydneyShare