基于免疫克隆模拟退火算法的网络生存性研究  

Study of network survivability based on immune clonal simulated annealing algorithm

作　　者：段谟意[1] 

机构地区：[1]南京铁道职业技术学院软件学院,江苏南京210031

出　　处：《计算机工程与设计》2012年第12期4436-4439,共4页Computer Engineering and Design

基　　金：全国教育科学"十二五"规划教育部规划课题阶段性研究成果基金项目(FJB110092)

摘　　要：针对通信网络产生的拥塞问题,基于免疫克隆模拟退火算法提出了一种新的网络生存性评价方法 (survivabilityalgorithm based on immune clonal simulated annealing,SAICSA)。该方法通过建立克隆变异和克隆交叉操作规则,并结合模拟退火接受准则来获得退火温度趋于零时的最优解。同时,以实际数据进行仿真实验,深入研究了网络生存性与失效边数、初始温度等影响因素之间的关系。实验结果表明,相比于免疫规划模拟退火算法和遗传模拟退火算法,SAICSA算法表现出较好的适应性。In order to mitigate the network congestion by node failures, a novel survivability evaluation method （Survivability Al- gorithm based on Immune Clonal Simulated Annealing, SAICSA） is proposed by immune clonal simulated annealing algorithm. In this method, the clonal variation and clonal intersection regulations are presented at first, and the optimal solution is got by simulated annealing regulation when annealing temperature is tended to zero. Then, simulation was conducted to study the rela- tionship between network survivability and failures node, as well as initial temperature with actual data. Compared SAIP （Simu- lated Annealing algorithm based on Immune Programming） and GSA （Genetic Simulated Annealing） algorithm, SAICSA algo- rithm has better adaptability.

关 键 词：生存性 免疫克隆模拟退火 失效 变异 交叉 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]