Abstract: Electronic jamming represses successfully threat target which plays a key role for penetration battle, aiming at the shortcomings of the optimization model on ideal environment, considering constraint condition and interference requirements on the practical battle, constructing the model of optimal allocation on jamming target, when constraint and parameters increase constantly, the traditional algorithm is very slow, which can’t even get the optimal solution. So introduce genetic algorithm, improve encoding, chromosome and design of genetic operators. The concrete example is given to construct model and the result is given, comparing with simulation annealing algorithm analysis, the results show that the improved genetic algorithm to search speed and reliability of the optimal solution is better than that of the simulated annealing algorithm. The optimal solution of interference target and scientific decision for realization of the optimization interference suppression efficiency are provided.

Key words: jamming repressing, distribution model, genetic algorithm, simulated annealing algorithm

摘要： 电子干扰成功压制威胁目标对突防作战起着关键性的作用，针对理想环境下优化模型的不足，考虑到实战环境下的约束条件和干扰需求，构建了干扰目标的优化分配模型；对于参变量和约束条件增多时，传统算法求解速度慢，甚至无法求得最优解，为此，引入遗传算法，改进编码、染色体和遗传算子的设计，通过具体算例建立模型和求解，并与模拟退火算法进行比较分析，结果表明改进遗传算法搜索最优解的速度和可靠性都优于模拟退火算法。最后给出了干扰目标分配的最优方案，为实现干扰的最佳压制效能提供了科学决策。

关键词: 干扰压制, 分配模型, 遗传算法, 模拟退火算法