Optimal routing, loading and aborting of UAVs executing both visiting tasks and transportation tasks

This paper investigates some cooperative Unmanned Aerial Vehicles (UAVs) executing both visiting tasks and transportation tasks. The UAVs are subject to random shocks which may harm both the cargoes on the UAVs and the UAVs themselves. In case an UAV is destructed, subsequently, all the cargoes it carries will be damaged. Furthermore, if only some cargoes on an UAV are damaged but the UAV itself is still functional, then the UAV can still continue its visiting tasks. In order to reduce the probability of UAV destruction, an UAV is allowed to abort its task if it is found to have suffered too many shocks after finishing the visit of a certain number of targets. For each given strategy of UAV routing and loading, the optimal aborting strategy needs to take into consideration both the expected cost due to UAV destruction and the expected cost due to unfinished tasks. Eventually, the optimal UAV routing and loading strategy can be solved assuming that the optimal aborting strategy is always adopted, with the objective to minimize the total cost of UAVs destruction, total cost of damaged cargoes, and the expected cost of unvisited targets. Monte Carlo simulation is applied to evaluate the cost of damaged cargoes, and tabu search algorithm is employed to optimize the routing of UAVs. Case studies are shown to illustrate the application of the framework.