网络静态结构韧性度参数空间高效搜索仿真  

High-Efficient Search and Simulation for Flexible Parameter Space of Static Structure of Network

作　　者：邱红艳[1] 陈烽[2] QIU Hong-yan;CHEN Feng(College of Computer Engineering,Chongqing College of Humanities,Science&Technology,Chongqing 401524,China;College of Information Engineering,Xizang University for Nationalities,Xianyang Shanxi 712082,China)

机构地区：[1]重庆人文科技学院计算机工程学院,重庆401524 [2]西藏民族大学信息工程学院,陕西咸阳712082

出　　处：《计算机仿真》2020年第5期389-393,共5页Computer Simulation

摘　　要：由于传统穷举搜索方法没有考虑在静态网络发生断裂之后剩余的网络状态,且搜索方法时间复杂度较高。为此提出基于遗传算法的韧性度采纳数空间高效搜索方法。在考虑静态网络发生断裂之后剩余的网络状态的情况下用图论表示法描述静态网络,通过韧性度评价网络静态结构脆弱性。编码网络静态结构中的节点空间,将原有对点割集变成对网络节点的高效搜索,采用网络离散度表示适应度函数,依照适应度函数的指示,采用交叉、选择和变异等方式,改进解空间中的可行解移动轨迹和移动趋势,得到最优解,完成网络静态结构韧性度参数空间高效搜索。经过仿真分析发现,上述方法在节点数20时收敛代数和收敛时间最小,最小值分别是41次和67 ms,即该方法搜索性能较好。This article presented an efficient search method of tenacity parameter space based on genetic algorithm. By considering the remaining network state after static network fracture, the static network was described by graph representation, the network vulnerability of static structure was evaluated by tenacity degree. The node space in network static structure was coded, and the original cut-set of nodes was changed into the efficient search for network nodes. Moreover, the network discrete degree was used to denote the fitness function. According to the instruction of fitness function, cross, selection and mutation were used to improve the movement track and movement trend of feasible solution in solution space, so as to find the optimal solution. Finally, high-efficient searching for tenacity parameter space of network static structure was completed. Through simulation analysis, it is found that the proposed method has the minimum convergence algebra and convergence time when the number of nodes is twenty. The minimum convergence algebra is forty-one and minimum convergence time is 67 ms. Therefore, this method has good search performance.

关 键 词：网络 静态结构 韧性度参数 空间高效搜索 遗传算法 适应度函数 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]