Multi-Objective Location Optimization of Drone Vertiports Considering Hierarchical Economic Feasibility

Fujian Jia; Manzhen Duan

doi:10.6919/ICJE.202608_12(8).0016

Authors

Fujian Jia School of Emergency Management and Safety Engineering, North China University of Science and Technology, Tangshan 063210, China
Manzhen Duan School of Emergency Management and Safety Engineering, North China University of Science and Technology, Tangshan 063210, China

DOI:

https://doi.org/10.6919/ICJE.202608_12(8).0016

Keywords:

Drone Logistics; Vertiport Location; Hierarchical Economic Threshold; Pareto Decision-Making.

Abstract

To address the efficiency bottleneck in urban last-mile delivery and the limitations of existing drone vertiport location models-which neglect the structural cost differences between urban and rural logistics and are sensitive to dimensional disparities in Pareto solution ranking-this paper proposes a multi-objective location optimization model and decision-making method for drone vertiports that considers hierarchical economic feasibility, providing a location decision tool for drone logistics distribution. The model maximizes demand coverage and minimizes total life-cycle cost, introducing a hierarchical economic feasibility threshold based on the distance from each demand point to its nearest logistics node, along with a hard capacity constraint. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) with elitist strategy is employed for solution, and a Nadir-Ideal Point Bidirectional Normalization method is proposed for Pareto solution ranking. The model is validated using real-world data from Caofeidian District, comprising 364 demand points and 10 traditional logistics nodes. After 800 generations, 110 non-dominated solutions are obtained. The recommended scheme constructs 11 vertiports, covering 55.77% of demand points, with a five-year total life-cycle cost of approximately 11.98 million CNY, achieving a 44.87% daily operating cost saving compared to traditional delivery. Sensitivity analysis reveals that the hierarchical threshold improves coverage in remote areas by 13.6 percentage points compared to a uniform threshold. The hierarchical economic feasibility threshold effectively identifies the substitution value of drones in remote areas, and the Nadir-Ideal Point Bidirectional Normalization method effectively eliminates the interference of dimensional differences on Pareto decision-making. The model and algorithm provide valuable support for scientific site selection of drone vertiports.

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