摘要
针对DDE-MRR算法存在的过早成熟和收敛过慢等缺陷,提出了一种新的DDE算法,用于电子对抗中协同干扰资源分配问题的求解。该算法首先依据协同干扰资源分配问题中存在的D/N不对等现象,重构了种群样本,然后基于DE/best/1策略对种群样本进行变异操作,最后通过贪婪机制实现样本更新。设计了3组仿真实验,对改进算法的收敛性和数值结果进行了验证分析,结果表明:改进算法收敛速度更快、计算结果更优,能够较好地解决电子对抗中的协同干扰资源分配问题,具备一定的实用价值。
To overcome the defects of the slow convergence speed and precocity of Discrete Differential Evolution （DDE）-MRR algorithm, a new DDE algorithm is proposed to solve the Cooperative Jamming Resource Allocation （CJRA） problem in electronic countermeasures. Firstly, the samples of the species group are reconstructed based on the inequality of D/N in CJRA problem. Secondly, the DE/best/1 strategy is used for mutation operation. Finally, the sample refreshment is implemented by greedy strategy. Three experiments are designed to analyze the convergence and numerical performance, and the results show that the proposed algorithm is more efficient and has practical value for solving the CJRA problem.
出处
《电光与控制》
北大核心
2018年第2期107-110,共4页
Electronics Optics & Control
基金
北京高等学校青年英才计划项目(YETP1503)
北京市教育委员会科技计划面上项目(KM201511232016)
关键词
电子对抗
差分进化算法
变异策略
资源分配
electronic countermeasures
differential evolution algorithm
mutation strategy
resource allocation
