Dynamic air tasking evaluation in a simulated network-centric battlespace

Joint Air Operations (JAO) are historically designed through centralised planning using static air tasking that assigns air assets to mission packages for the purpose of achieving campaign objectives. The current methodology cannot anticipate changes in the battlespace nor take advantage of real-time information. In this study, we develop a simulation model of the battlespace that utilises a Multi-Criteria Decision Analysis (MCDA) model to assign vehicles to targets by considering four competing objectives (effort, effectiveness, efficiency, and connectivity). A Voronoi network is used to determine the paths of vehicles to their assigned targets and network optimisation is used to validate the quality of the assignments. The results indicate that dynamic air tasking is considerably more effective and more efficient than static air tasking.

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