Multi-objective vertiport location optimization for a middle-mile package delivery framework: Case study in the South Holland Region

Abstract

With the rapidly increasing pace of urbanization and high demand for efficient modes of transport, the Urban Air Mobility (UAM) market has seen a remarkable growth in the past years. This is especially the case for the transportation of goods. Using UAM for cargo operations is likely through operating on Middle-Mile Delivery (MMD) missions to transport cargo between facilities or distribution centers in an operator’s network. The efficiency and practicality of such a network are largely affected by the selection of strategic positions for vertiports. As vertiport location optimization is underexplored in current scientific research this paper aims to fill this research gap by developing and analyzing a multi-objective optimization model for the placement of vertiports for a middle-mile package delivery system, considering capacity, available land space, safety and noise impact factors. We develop a novel Multi-Objective Multiple Allocation Capacitated p-Hub Coverage Problem framework for an MMD UAM network and test it using the South Holland region as a case study. Notably, the model can easily be converted to other cities. First, to reduce computational efforts, the K-means clustering algorithm is proposed. This is used to divide 6625 zones into a number of K clusters, with each cluster representing a vertiport candidate location. Furthermore, we present a multi-objective Tabu Search based heuristic optimization algorithm to solve the optimization problem. The impact of different factors such as number of clusters, number of vertiports, drone range, maximum safety distance, and turn around time The presented model provides decision-makers with the ability to assess the suitability of a region for the implementation of a UAM MMD system and aids in the identification of potential good locations to set up vertiports. We demonstrate that an increase in the number of vertiports leads to a higher attainable demand coverage, however, this results in a steep drop-off in terms of safety and noise nuisance performance. Furthermore, the results show that an increase in drone range, maximum safety distance or a decrease in turn around time allow for overall better performing vertiport networks.