Simulation modeling with event graphs
Communications of the ACM
Simple movement and detection in discrete event simulation
WSC '05 Proceedings of the 37th conference on Winter simulation
Dynamic allocation of fires and sensors (DAFS): a low-resolution simulation for rapid modeling
Proceedings of the 38th conference on Winter simulation
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
A normalized weighted entropy measure for sensor allocation within simulations
Winter Simulation Conference
Assessing the robustness of UAV assignments
Proceedings of the Winter Simulation Conference
Energy Management in Swarm of Unmanned Aerial Vehicles
Journal of Intelligent and Robotic Systems
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Many military planning problems are difficult to solve using pure mathematical programming techniques. One such problem is scheduling unmanned aerial vehicles (UAVs) in military operations subject to dynamic movement and control constraints. This problem is instead formulated as a dynamic programming problem whose approximate solution is obtained via the Assignment Scheduling Capability for UAVs (ASC-U) model using concepts from both simulation and optimization. Optimization is very effective at identifying the best decision for static problems, but is weaker in identifying the best decision in dynamic systems. Simulation is very effective in modeling and capturing dynamic effects, but is weak in optimizing from alternatives. ASC-U exploits the relative strengths of both methodologies by periodically re-optimizing UAV assignments and then having the simulation transition the states according to state dynamics. ASC-U thus exploits the strengths of simulation and optimization to construct good, timely solutions that neither optimization nor simulation could achieve alone.