Abstract:

Aiming at the problem of waste of weapon resources in traditional weapon target assignment (WTA), and to realize the maximum benefit of target and network attacks and the minimum consumption of weapons, we establish a multi-objective WTA model, which takes the damage probability constraint into consideration. We improve the standard quantum immune clonal multi-objective optimization algorithm (QICMOA), introduce the chaos mechanism, and repair the infeasible solutions. We also make improvement for the search strategy and diversity maintaining strategy and design an improved QICMOA. Simulation experiments verify the correctness of the model and the superiority of the algorithm. Compared with the traditional QICMOA, the performance of the new algorithm is improved by 23% on average.

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