A Greedy Ant Colony System for Defensive Resource Assignment Problems

ABSTRACT The weapon-target assignment (WTA) problem is crucial for strategic planning in military decision-making operations. It defines the best way to assign defensive resources against threats in combat scenarios. This is a NP-complete problem where no exact solution is available to deal with all possible scenarios. A critical issue in modeling the WTA problem is the time performance of the developed algorithms, subject only recently contemplated in related publications. This paper presents a hybrid approach which combines an ant colony optimization with a greedy algorithm, called the Greedy Ant Colony System (GACS), in which a multi colony parallel strategy was also implemented to improve the results. Aiming at large scale air combat scenarios, simulations controlling the algorithm time performance were executed achieving good quality results.

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