The vehicle routing problem
On the influence of GVR in vehicle routing
Proceedings of the 2003 ACM symposium on Applied computing
A genetic algorithm for unmanned aerial vehicle routing
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Multi-Objective Genetic Algorithms for Vehicle Routing Problem with Time Windows
Applied Intelligence
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Assessing the robustness of UAV assignments
Proceedings of the Winter Simulation Conference
4D trajectory planning in ATM with an anytime stochastic approach
Proceedings of the 3rd International Conference on Application and Theory of Automation in Command and Control Systems
Journal of Intelligent and Robotic Systems
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This investigation develops an innovative algorithm for multiple autonomous unmanned aerial vehicle (UAV) mission routing. The concept of a UAV Swarm Routing Problem (SRP) as a new combinatorics problem, is developed as a variant of the Vehicle Routing Problem with Time Windows (VRPTW). Solutions of SRP problem model result in route assignments per vehicle that successfully track to all targets, on time, within distance constraints. A complexity analysis and multi-objective formulation of the VRPTW indicates the necessity of a stochastic solution approach leading to a multi-objective evolutionary algorithm. A full problem definition of the SRP as well as a multi-objective formulation parallels that of the VRPTW method. Benchmark problems for the VRPTW are modified in order to create SRP benchmarks. The solutions show the SRP solutions are comparable or better than the same VRPTW solutions, while also representing a more realistic UAV swarm routing solution.