An efficient algorithm for multi-modal skyport location problem with choice-based demand

Abstract

This study presents the operation of urban air mobility (UAM), an innovative transportation technology aimed at alleviating traffic congestion in cities. A key consideration for the successful introduction and efficient operation of the transportation is to decide on locations of skyports, which are stations for vertical take-off and landing of air mobility. In this study, we cover a skyport location problem incorporating choice probabilities of transportation modes for each user by applying a binary logit model. The choice probabilities are predicted by considering factors such as fare, travel time, and social acceptance. We propose two mathematical formulations associated with the skyport location problem; one is to maximize the proportion of users who choose the UAM service and the other is to minimize the total sum of the travel time. The two models are NP-hard problems, necessitating an effective and efficient solution methodology for the problem. This study presents a methodology based on a cross-entropy algorithm, which is known for efficiently solving combinatorial optimization problems. We also validate the good performances of the solution methodology through numerical experiments.