  Recently, an unmanned aerial vehicle (UAV), as known as drone, has become an
alternative means of package delivery. Although the drone delivery scheduling
has been studied in recent years, most existing models are formulated as a
single objective optimization problem. However, in practice, the drone delivery
scheduling has multiple objectives that the shipper has to achieve. Moreover,
drone delivery typically faces with unexpected events, e.g., breakdown or
unable to takeoff, that can significantly affect the scheduling problem.
Therefore, in this paper, we propose a multi-objective and three-stage
stochastic optimization model for the drone delivery scheduling, called
multi-objective optimization for drone delivery (MODD) system. To handle the
the multi-objective optimization in the MODD system, we apply
$\varepsilon$-constraint method. The performance evaluation is performed by
using a real dataset from Singapore delivery services.
