Energy-Efficient Drone Logistics for Last-Mile Delivery: Implications of Payload-Dependent Routing Strategies
Ziyue Li, Qianwen (Vivian) Guo, Paul Schonfeld

TL;DR
This paper explores a novel energy-efficient drone routing approach for last-mile delivery, revealing counter-intuitive strategies and quantifying potential energy savings through numerical experiments.
Contribution
It introduces a green drone routing problem considering payload-dependent energy consumption, demonstrating strategies that outperform traditional distance-based routing.
Findings
Energy-aware routing can save up to 5.97% energy compared to distance minimization.
Longer routes may sometimes consume less energy than shorter ones.
Heterogeneous drone fleets can improve delivery efficiency.
Abstract
Drone delivery is rapidly emerging as a cost-effective and energy efficient alternative for last-mile delivery. Unlike ground vehicles, a drone's energy consumption depends on its payload in addition to travel distance. This creates a unique environmental challenge for multi-stop delivery tours, as the drone's total weight, and therefore its energy consumption rate, dynamically changes after each delivery. This paper investigates a novel green drone routing problem focused on maximizing energy efficiency. Through a series of motivating examples and numerical experiments, we demonstrate that energy-aware routing leads to several counter-intuitive routing strategies that contradict traditional distance-minimization delivery: a longer route may actually consume less energy than a shorter one; separate single-customer tours can be superior to a multi-stop tour; and a heterogeneous fleet,…
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