现代战争中,跨平台武器单元的协同利用,是合同编队体系的重要内容,作战方式也正由平台级协同向着能力要素级协同转变,这对武器目标分配问题的解决提出了更大挑战.本文将武器单元的最小划分单位细化到能力要素级,以毁伤概率与成本消耗为优化目标,面向多种来袭目标的编队防空场景,提出了跨平台武器目标分配算法.同时,基于混沌映射提出了混沌种群重构(chaotic population reconstruction,CPR)机制,并结合带存档的 自适应差分进化(adaptive differential evolution with optional external archive,JADE)算法提出 了 CPR-J ADE算法,利用CPR机制可以帮助算法在解决高维复杂约束问题时跳出局部最优.再将其运用到武器目标分配模型上,实现了对模型的高效求解.最后,通过在多种数据规模下与其他进化优化算法的仿真对比试验分析,验证了所提方法的正确性与有效性.
Cross platform weapontarget allocation method based on improved differential evolution algorithm
In modern warfare,the collaborative utilization of cross platform weapon units is an important content of the application of combined-arms formation system.The mode of operation is also changing from platform-level collaboration to capability-level element collaboration,which poses a greater challenge to the solution of the problem of weapon target allocation(WTA).Aiming at the optimization of damage probability and cost consumption,a cross platform WTA algorithm is proposed for formation air defense scenarios with multiple incoming targets,with the minimum division unit of weapon unit refined to the capability element level.At the same time,the chaotic population reconstruction(CPR)mechanism based on chaotic mapping is proposed.And the CPR adaptive differential evolution with optional external archive(JADE)algorithm is proposed combined with the JADE.The CPR mechanism can help the algorithm jump out of the local optimum when solving high-dimensional complex constraint problems.Then it is applied to the WTA model to realize the efficient solution of the model.Finally,by comparing with other evolutionary optimization algorithms under various data scales,the correctness and effectiveness of the proposed method are verified.
cross platform weapon target allocation(WTA)formation air defensechaotic mappingdifferential evolutionchaotic population reconstruction-adaptive differential evolution with optional external archive(CPR-JADE)algorithm
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维普
