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提出基于多目标决策理论的协同空战武器目标分配模型,并用进化多目标优化算法求解.空战是一个多阶段攻防过程,针对多数空战武器目标分配采用一次性完全分配、不考虑火力资源消耗等不足,构建多目标决策模型,在达到毁伤门限的前提下,同时对一次攻击后使敌编队的总期望剩余威胁最小和分配导弹消耗量最小两个目标函数寻优.提出用多目标离散粒子群-引力搜索算法(MODPSO-GSA)求解分配模型,该混合进化多目标优化算法结合二者优点,具有稳定的全局搜索能力并保证收敛到Pareto前沿.该算法可求得满足毁伤门限的不同耗弹量的分配方案最优解集以供指挥员决策参考.仿真算例验证了新模型及所提出MODPSO-GSA进化多目标优化求解算法的有效性.
This paper proposes a cooperative air combat weapon target assignment model based on multi-objective decision-making theory and is solved by evolutionary multi-objective optimization algorithm.Air combat is a multi-stage attack-defense process.Aiming at the deficiency of firepower resource consumption and so on, A multi-objective decision-making model is constructed, and under the precondition that the threshold of damage is reached, at the same time, two objective functions, which minimize the total expectation of the enemy formation and minimize the total missile distribution, are proposed.A multi-objective discrete particle swarm optimization Search algorithm (MODPSO-GSA) to solve the distribution model, the hybrid evolutionary multi-objective optimization algorithm combined with the advantages of both have a stable global search ability and ensure convergence to the Pareto front. The algorithm can be obtained to meet the different damage threshold consumption dose The optimal solution set is assigned to the commander for decision making.A simulation example verifies the effectiveness of the new model and the proposed MODPSO-GSA evolutionary multi-objective optimization algorithm.