基于改进量子免疫克隆多目标优化算法的火力分配问题.

针对传统火力分配中存在武資源像#•的情况，以对敌目标与网络攻击收益:最大、己方或.暮 消;耗、最小为I!标，建立一种考虑题侈概率.辫束条件的多目标火力分:配檬型s对标准量于免應克隆.多目标 优化算:法进抒傀化，引入了漉洗机制，修复不可行解，并对搜索策略和多样牲保持策略进行改进，豫计了一 种政迸妁童子免疫克證多目标优.化算:法。..通过粢猃.真，验证了•模•塑的正翁性与算法的优趙性。相比于 传统量予兔疫克，隆算法，改逢算法的性能平均提高了 23%. 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. [ABSTRACT FROM AUTHOR]