Drone-truck collaborative scheduling with simultaneous delivery and pickup under uncertainty

This work investigates a drone-truck collaborative scheduling problem, where customer packages may require delivery or pickup for transportation to the distribution center. In this study, the transportation speed of drones is subject to uncertainty arising from variables such as wind direction and intensity, etc. For solving the problem, a K-means with elbow method is firstly employed to cluster the 2D coordinate of customers, yielding cluster centers that represent the points requiring traversal by the truck. Subsequently, a mixed integer programming model with the objective of minimizing the weighted sum of the total transportation time and the total energy consumption of drones is formulated. For such the model, both the truck routing path and the drone scheduling plan for delivery and pickup are jointly optimized at the tactical level. To solve the model under uncertainty, a data-driven robust optimization approach is developed. Numerical experiments are conducted to demonstrate the effectiveness of our approaches.