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Optimal distribution of reliability for a large network based on connectivity
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作者 陈玲俐 于洁 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2008年第12期1633-1642,共10页
It is a non-polynomial complexity problem to calculate connectivity of the complex network. When the system reliability cannot be expressed as a function of element reliability, we have to apply some heuristic methods... It is a non-polynomial complexity problem to calculate connectivity of the complex network. When the system reliability cannot be expressed as a function of element reliability, we have to apply some heuristic methods for optimization based on connectivity of the network. The calculation structure of connectivity of complex network is analyzed in the paper. The coefficient matrixes of Taylor second order expansion of the system connectivity is generated based on the calculation structure of connectivity of complex network. An optimal schedule is achieved based on genetic algorithms (GA). Fitness of seeds is calculated using the Taylor expansion function of system connectivity. Precise connectivity of the optimal schedule and the Taylor expansion function of system connectivity can be achieved by the approved Minty method or the recursive decomposition algorithm. When error between approximate connectivity and the precise value exceeds the assigned value, the optimization process is continued using GA, and the Taylor function of system connectivity needs to be renewed. The optimization process is called iterative GA. Iterative GA can be used in the large network for optimal reliability attribution. One temporary optimal result will be generated every time in the iteration process. These temporary optimal results approach the real optimal results. They can be regarded as a group of approximate optimal results useful in the real project. 展开更多
关键词 optimal distribution of reliability connectivity genetic algorithms (ga approved minty method recursive decomposition algorithm
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大型网络基于连通可靠度的最优可靠度分配 被引量:2
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作者 陈玲俐 于洁 《应用数学和力学》 CSCD 北大核心 2008年第12期1486-1494,共9页
由于网络连通可靠度计算属于NP-hard问题,当系统可靠度无法显式表达时,基于连通可靠度的大型复杂网络优化通常只能采用启发式优化算法解决.通过对复杂网络连通可靠度算法结构的分析,给出了系统连通可靠度的Taylor方程.采用遗传算法,由... 由于网络连通可靠度计算属于NP-hard问题,当系统可靠度无法显式表达时,基于连通可靠度的大型复杂网络优化通常只能采用启发式优化算法解决.通过对复杂网络连通可靠度算法结构的分析,给出了系统连通可靠度的Taylor方程.采用遗传算法,由系统连通可靠度的Taylor方程确定种群适应值,得到一个系统最优可靠度分配方案;将最优解带入改进Minty算法或递推分解算法中,计算该最优解的连通可靠度精确值和对应的连通可靠度的Taylor展开方程;再次采用遗传算法求最优解.当最优解对应的可靠度精确值和Taylor方程算得得近似值误差小于指定精度时,则此最优解为最终的系统最优可靠度分配方案.将此优化过程称为迭代遗传算法.算例显示迭代遗传算法不仅可用于大型网络的连通可靠度最优分配,而且优化迭代过程中可以得到多组阶段最优解,这些解均落在最优解附近,构成了近似最优解群,在实际工程优化中拓展了选择面. 展开更多
关键词 最优可靠度分配 连通可靠度 遗传算法 改进minty算法 递推分解算法
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