求解协同干扰问题的高效免疫遗传算法  

Efficiently Immune Genetic Algorithm for Solving Cooperative Jamming Problem

作　　者：薛羽[1] 庄毅[1] 朱浩[2] 张友益 

机构地区：[1]南京航空航天大学计算机科学与技术学院,南京210016 [2]南通大学计算机科学与技术学院,江苏南通226019 [3]中船重工集团公司第723研究所,江苏扬州225001

出　　处：《电子科技大学学报》2013年第3期453-458,共6页Journal of University of Electronic Science and Technology of China

基　　金：江苏省普通高校研究生科研创新计划(CXLX11_0203);航空基金(05F2037);国防基础研究基金(Q072006C002-1)

摘　　要：为协同干扰武器目标分配问题建立的数学模型,当问题规模增大时,现有的智能求解算法表现出两点不足,一是所求解质量下降;二是求解速度不可接受。针对该两点不足提出了具有贪婪修复过程的免疫遗传算法,算法设计了通用十进制扩展编码方案、基于免疫的轮盘赌选择算子和贪婪修复算子。仿真实验表明,该算法与现有算法相比具有明显的效率优势,在解决大规模协同干扰武器目标分配问题时不仅解算时间可接受而且所求解质量比同类算法高。This paper provides a mathematical model for cooperative jamming weapon target assignment problem. The existing intelligent optimization algorithms have two defects, i.e., with the scale of the problem increases, the quality of the solutions obtained by existing algorithms decreases and the calculate time the algorithms spent to find the optimal solutions becomes unacceptable. Therefore, an efficient immune genetic algorithm is proposed in this paper. In the proposed algorithm, an extended decimal coding scheme, an immune mechanism based roulette wheel selection operator, and a greedy repair operator are designed. Simulation experimental results indicate that the proposed algorithm is more efficient and effective than its competitors, and it can obtain ootimal solutions with highly quality within acceptable time.

关 键 词：人工免疫系统 组合优化 智能计算 协同干扰 遗传算法 武器目标分配 

分 类 号：TP309.02[自动化与计算机技术—计算机系统结构]