Problem
Research questions and friction points this paper is trying to address.
energy-efficient drone routing
payload-dependent energy consumption
last-mile delivery
green logistics
multi-stop drone tours
Energy-Efficient Drone Logistics for Last-Mile Delivery: Implications of Payload-Dependent Routing Strategies
🤖 AI Summary
This study addresses the challenge of energy inefficiency in drone last-mile delivery caused by dynamically varying payloads, which renders conventional shortest-path planning suboptimal for energy consumption. The authors propose a payload-dependent, energy-aware path planning approach that integrates a dynamic payload-energy consumption model with numerical optimization to compare minimum-distance and minimum-energy strategies. Counterintuitive insights emerge: longer routes can be more energy-efficient, serving single customers per flight may outperform multi-stop consolidation, and matching heterogeneous drone fleets to specific delivery demands enhances overall energy efficiency. Experimental results demonstrate that the proposed method achieves energy savings in 67% of test instances, with an average reduction of 2.17% and a maximum of 5.97%, thereby significantly improving the sustainability of drone-based delivery operations.
📝 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, with drones of varying sizes, can achieve greater efficiency by matching drone capacity to specific delivery demands. In the numerical study, the green routing strategy shows energy savings in 67% of the instances. For these cases, the average energy saving is 2.17%, with a maximum saving of 5.97%, compared to minimum distance routing. These findings highlight the potential for green drone routing strategies to improve the sustainability of last-mile delivery.
Innovation
Methods, ideas, or system contributions that make the work stand out.
energy-efficient routing
payload-dependent energy consumption
green drone logistics
heterogeneous drone fleet
last-mile delivery
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