  Quantum computing promises significant improvements of computation
capabilities in various fields such as machine learning and complex
optimization problems. Recent technological advancements suggest that the
adiabatic quantum computing ansatz may soon see practical applications. In this
work, we adopt this computation paradigm to develop a quantum computation based
solver of the well-known weapon target assignment problem, an NP-hard nonlinear
integer programming optimization task. The feasibility of the presented model
is demonstrated by numerical simulation of the adiabatic evolution of a system
of quantum bits towards the optimal solution encoded in the model Hamiltonian.
Over all, the described method is not limited to the context of weapon
management but is, with slight modifications to the model Hamiltonian,
applicable to worker-task allocation optimization in general.
