Reliability Based-model for Optimizing Routing of Truck-drone Delivery System

This study develops a reliability-based optimization model for routing of truck-drone delivery systems, where trucks transport goods from a central warehouse to depots and drones perform last-mile deliveries. Drone failures are modeled as exponentially distributed events that may result in partial or complete loss of customer demand. An optimization model is formulated to identify feasible routes that minimize expected demand loss and optimizes truck depot assignments to ensure overall system reliability. A demonstrated example with two depots, three drones, two trucks, and six customers was conducted. Initially, 41 feasible paths were evaluated. Then, three paths were determined with a minimum expected loss of 0.1999, with a total travel time of 50.207 minutes. When optimizing for travel time, only one depot was selected to serve all the six customers using two drones, yielding a total travel time of 46.55 minutes and an expected loss of 0.2179. The results demonstrate that considering reliability of the delivery system significantly influence the routing decisions.