吉首大学学报(自然科学版)

• 物理与电子 • 上一篇    下一篇

可靠性约束函数未知的网路费用最小化快速求解

陈丽,王景芹   

  1. (河北工业大学电磁场与电器可靠性省部共建重点实验室,天津 300130)
  • 出版日期:2016-07-25 发布日期:2016-07-19
  • 作者简介:陈丽(1980—),女,安徽肖县人,河北工业大学博士生,讲师,主要从事复杂系统与可靠性研究.
  • 基金资助:

    国家自然科学基金资助项目(51077039)

Fast Algorithm for Solving Cost Minimization Problem of Complex System with Unknown Constrained Reliability Function

CHEN Li,WANG Jingqin   

  1. (Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability,Hebei University of Technology,Tianjin 300130,China)
  • Online:2016-07-25 Published:2016-07-19

摘要:

针对现代网络可靠性约束函数未知的网络费用最小化问题,提出基于在线SVM和MCS技术的快速求解算法.该算法由Monte Carlo仿真方法模拟网络可靠度值,由量子粒子群算法搜寻目标全局最优解,并充分利用MCS技术模拟的可靠性信息,在线建立SVM可靠性评估模型,借助SVM模型评估后续搜寻解的可行性,减少MCS模拟次数和求解时间.与Yeh方法相比,在可靠性模拟精度为0.01的条件下,模拟次数和求解时间都缩小近1个数量级.

关键词: 复杂网络, 费用最小化, Monte Carlo仿真, 支持向量机, DPSO算法, 最优化

Abstract:

Aiming at the cost minimization problems of modern networks with unknown constrained reliability function,a fast solving algorithm is proposed based on the Monte Carlo Simulation (MCS) technique and the Support Vector Machine (SVM) technique.The proposed algorithm uses MCS technique to obtain the reliability values of complex network,and then uses Quantum Particle Swarm Optimization (DPSO) algorithm to search for the global optimal minimal value. With the reliability information previously obtained by MCS,the online SVM  evaluation model of network reliability is constructed to determine the feasibility of the subsequent solutions,reducing the MCS simulating frequencies and solving time.Experiment results verify that,compared with Yeh's method and with 0.01 reliability simulation precision,the MCS frequencies and the solving time decrease by almost one order of magnitude.

Key words: complex network, cost minimization, Monte Carlo simulation, support vector machine, QPSO algorithm

公众号 电子书橱 超星期刊 手机浏览 在线QQ