Reactive tabu search in unmanned aerial reconnaissance simulations
Proceedings of the 30th conference on Winter simulation
The vehicle routing problem
A multi-objective-based non-stationary UAV assignment model for constraints handling using PSO
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part II
Simultaneous sensor selection and routing of unmanned aerial vehicles for complex mission plans
Computers and Operations Research
Heuristics for determining a patrol path of an unmanned combat vehicle
Computers and Industrial Engineering
Assessing the robustness of UAV assignments
Proceedings of the Winter Simulation Conference
On the Concerted Design and Scheduling of Multiple Resources for Persistent UAV Operations
Journal of Intelligent and Robotic Systems
Energy Management in Swarm of Unmanned Aerial Vehicles
Journal of Intelligent and Robotic Systems
Stochastic resource allocation using a predictor-based heuristic for optimization via simulation
Computers and Operations Research
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This paper considers the strategic routing of a fleet of unmanned combat aerial vehicles (UCAVs) to service a set of predetermined targets from a prior surveillance mission. Targets are characterized by their priority or importance level, and minimum and maximum service levels that, respectively, represent the lower bound of munitions for destruction and upper bound of munitions to limit collateral damage. Additional constraints to be respected are the payload capacities of the (possibly heterogeneous) UCAV fleet and the range based on fuel capacity and payload transported. The vital aspect of this paper is the integrated optimal utilization of available resources-weaponry and flight time-while allocating targets to UCAVs and sequencing them to maximize service to targets based on their criticality. The complexity of the problem is addressed through a decomposition scheme with two problems: a target assignment problem (modeled as a minimum cost network flow problem) and a vehicle routing problem, which in turn splits into multiple decision traveling salesman problems, one for each UAV. A Tabu search heuristic is developed to coordinate the two problems. Using test problems we establish the applicability of this approach to solve practical-sized problems.