An empirical investigation of the static weapon-target allocation problem

The allocation of weapons to targets (such as missiles and hostile aircrafts) is a well-known resource allocation problem within the field of operations research. It has been proven that this problem, in general, is NP-complete. For this reason, optimal solutions to the static weapon-target allocation (WTA) problem can not be obtained in real-time for large-scale problems. We try to find the limit for how large problems that can be solved optimally in real-time by exhaustive search algorithms through running empirical experiments. We also propose a heuristic genetic algorithm for solving larger-scale problems.

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