基于TS-NGA的多作战智能体制导-攻击匹配优化  

An Optimized Guidance-Attack Aerial Matching Method for Multiple Combat Agents Based on TS-NGA

作　　者：万路军[1] 姚佩阳[1] 贾方超[1] 马方方[1] 

机构地区：[1]空军工程大学信息与导航学院,西安710077

出　　处：《电光与控制》2013年第10期1-6,共6页Electronics Optics & Control

基　　金：国家自然科学基金(70771157);2011年度和2012年度全军军事学研究生课题;空军工程大学博士创新基金(KGD2011-002)

摘　　要：空中制导-攻击匹配(GAM)旨在确定武器单元、制导单元以及目标三者之间的最优匹配关系,以使多作战智能体任务联盟整体作战效能最大。分析了基于混合通信方式的多作战智能体制导-攻击匹配过程,建立制导攻击匹配约束优化问题模型,设计了一种禁忌策略的嵌套遗传算法(TS-NGA)对模型进行求解,算法的外层循环寻求武器单元和制导单元的最优配对,内层循环寻求武器单元和目标的最优配对。针对GAM问题特点,制定了编码与解码策略、交叉、变异规则以及选择、禁忌策略。仿真实验结果表明所设计求解算法能较好地解决三维变量的GAM问题模型。The aerial Guidance-Attack guidance units and targets in order to Matching （GAM） focuses on the maximize the effectiveness of the allocating of weapon units, multiple combat agents＇ task coalition. The guidance-attack matching process of multiple combat agents based on integrated communication mode was analyzed, a constrained optimization model was proposed for the problem and the nested genetic algorithm based on tabu policy was designed to solve the model. The outer-loop of GA was used to search for the optimum weapon-guidance matching and the inner-loop of GA used to search for the optimum weapon- target allocation. Considering the discrete characteristics of the problem, the coding rules, crossover operators, mutation operators and tabu policy were designed. The experimental results show that the proposed algorithm can solve the three-dimensional variable GAM problem effectively.

关 键 词：协同空战 作战智能体 协同制导 嵌套遗传算法 匹配优化 

分 类 号：V271.4[航空宇航科学与技术—飞行器设计]