基于启发式遗传算法的近距空中支援超网络结构优化

Optimization of close air support super-network structure based on heuristic genetic algorithm

基于超网络理论建立集申请网、情报网、指控网、协调网和火力网于一体的CAS超网络模型;以提高网络抗毁性和网络效率为优化目标,在标准遗传算法的基础上,根据CAS超网络模型得到启发式信息,对其初始化生成初始种群,对关键节点和普通节点设置不同的变异概率,通过遗传算法求解运算;仿真分析函数的寻优性能和优化前后网络的拓扑指标。结果表明,优化后的CAS超网络结构抗毁性更强、网络流转效率更高。

A CAS super-network model was established based on the super-network theory,which integrated application network,intelligence network,command and control network,coordination network and firepower network.Improving the network anti-destroying ability and network efficiency was taken as the optimization goal.Based on the standard genetic algorithm,the heuristic information was obtained according to the CAS super-network model,and the information was initialized to generate an initial population.The key nodes and common nodes are set to different mutation probabilities,and the calculation result was solved by genetic algorithm.The optimization performance of the function and the topology indicators of the network before and after optimization were simulated and analyzed.The results show that the optimized CAS super-network structure has better anti-destroying ability and network flowing efficiency.