A branch and bound algorithm for the traveling salesman and the transportation routing problems
Computers and Industrial Engineering
Parallel simulation of UAV swarm scenarios
WSC '04 Proceedings of the 36th conference on Winter simulation
Proceedings of the 38th conference on Winter simulation
Priority-based assignment and routing of a fleet of unmanned combat aerial vehicles
Computers and Operations Research
Validating a network simulation testbed for army UAVs
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Simulation-aided path planning of UAV
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Multi-objective UAV mission planning using evolutionary computation
Proceedings of the 40th Conference on Winter Simulation
Elementary Statistics Using JMP
Elementary Statistics Using JMP
| Hi-index | 0.00 |
The deployment of unmanned aerial vehicles (UAV) is increasingly commonplace. UAVs support military forces by flying over dangerous zones mainly for surveillance missions. Route planning for UAVs is therefore a critical problem. With many side constraints such as visitation time requirements, mission priorities, and vehicle capabilities, route planning is a hard problem. Heuristic approaches have therefore been developed to construct near optimal routes. Given the hostile operating conditions, however, robustness of these plans is emerging as a more significant concern than optimality. This paper thus investigates the robustness of constructed UAV routes. To this end, a greedy assignment algorithm that takes into consideration physical constraints and operational risks is used to construct UAV tours. The sensitivity of these tours to various operational parameters such as mission threat level, weather risk, and crash rates as well as their interactions is assessed in a simulation study through a set of designed experiments.