Multi-Objective Design of UAS Air Route Network Based on a Hierarchical Location-Allocation Model

This research concentrates on the Unmanned Aircraft System (UAS) demand sites' hierarchical location-allocation problem in air route network design. With demand sites (locations where UAS operations are requested) organized and allocated according to the spatial hierarchy of UAS traffic flows, the hierarchical structure guarantees resource conservation and economies of scale through traffic consolidation. Therefore, in this paper, the UAS route network with a three-level hierarchy is developed under a multi-objective decision-making framework, where concerns about UAS transportation efficiency from the user side and construction efficiency from the supplier side are both simultaneously considered. Specifically, a bi-level Hybrid Simulated Annealing Genetic Algorithm (HSAGA) with global and local search combined is proposed to determine the optimal number, location, and allocation of hierarchical sites. Moreover, using the information of site closeness and UAS demand distribution, two problem-specific local search operators are designed to explore elite neighborhood regions instead of all the search space. A case study based on the simulated UAS travel demand data of the Beijing area in China was conducted to demonstrate the effectiveness of the proposed method, and the impact of critical parameter settings on the network layout was explored as well. Findings from this study will offer new insights for UAS traffic management in the future.