空军工程大学学报（自然科学版）2016，Vol.17Issue(4)：29-34,6.DOI:10.3969/j.issn.1009-3516.2016.04.006
基于网络对抗火力分配的改进量子免疫克隆算法
Improved Quantum Immune Clonic Algorithm in Weapon-Target Assignment under Conditions of Network Confrontation Environment
摘要
Abstract
In consideration of the principles that attack benefits of network combined targets with targets are maximal and its own consumption is minimal in total,a multi-obj ective optimization model is estab-lished under conditions of network confrontation environment in fire distribution.Under conditions of ran-dom network topology introduced,the effect of fire distribution corresponding to the random network is analyzed.This paper adopts quantum-inspired immune clonic multi-obj ective optimization algorithm to solve the model of fire distribution.Though experimental simulation,the change circumstances of the total attack benefits are analyzed by using different cost ammunition.The attack efficiency of the fire distribu-tion scheme increases by 23% by using the improved algorithm over the fire distribution scheme by using standard algorithm.The convergence of the algorithm and superiority of Pareto solution distribution are studied.The experiments demonstrate that the Pareto efficiency solution distribution increases 42% by u-sing the improved algorithm over using the standard algorithm.The superiority of the model and the effi-ciency of the algorithm are verified.关键词
火力分配/量子克隆免疫多目标算法/复杂网络/网络中心战/Pareto最优解Key words
weapon-target assignment/QICMOA/complex networks/network-centric warfare/Pareto effi-ciency分类
计算机与自动化引用本文复制引用
冯超,景小宁,李秋妮,夏菲,费凯..基于网络对抗火力分配的改进量子免疫克隆算法[J].空军工程大学学报（自然科学版）,2016,17(4):29-34,6.基金项目
国家自然科学基金(71501184) （71501184）
航空科学基金(20155196022) （20155196022）
