Vertiport Locations Optimization in Discrete Search Space

This paper aims to find optimal vertiport locations for an urban air mobility service in a metropolitan area. This location optimization problem has no specific candidates, so its search space is finely discretized. The optimal locations are defined as the set of locations that maximize the total revenue. To estimate the revenue, actual traffic data and a mode choice model are used to forecast the demand. Since the search space of the location optimization problem is huge, a local search-based algorithm is proposed to find a near-optimal solution in a short computation time. The proposed algorithm is applied to the Seoul metropolitan area, Republic of Korea, and the optimal vertiport network is found. This paper also analyzes the impact of operational parameters, such as the number, distance, and catchment area of vertiports and the fare and speed of aircraft, at the optimal locations. The results of this study can provide insights to stakeholders.