  Highly populated cities face several challenges, one of them being the
intense traffic congestion. In recent years, the concept of Urban Air Mobility
has been put forward by large companies and organizations as a way to address
this problem, and this approach has been rapidly gaining ground. This
disruptive technology involves aerial vehicles (AVs) for hire than can be
utilized by customers to travel between locations within large cities. This
concept has the potential to drastically decrease traffic congestion and reduce
air pollution, since these vehicles typically use electric motors powered by
batteries. This work studies the problem of scheduling the assignment of AVs to
customers, having as a goal to maximize the serviced customers and minimize the
energy consumption of the AVs by forcing them to fly at the lowest possible
altitude. Initially, an Integer Linear Program (ILP) formulation is presented,
that is solved offline and optimally, followed by a near-optimal algorithm,
that solves the problem incrementally, one AV at a time, to address scalability
issues, allowing scheduling in problems involving large numbers of locations,
AVs, and customer requests.
