考虑节点综合重要度的物流网络级联失效模型

为提高突发事件级联失效对物流网络破坏程度的评估的可信性,提出一个考虑物流网络边权特征的节点重要度的综合度量方法,并在此基础上构建相应的级联失效模型。数值仿真结果表明：该模型对于物流节点重要度的衡量更为完善,所制定的失效负载分流准则及其对于级联失效破坏性的评估结果更具合理性。通过该模型可更加全面地掌握了解网络结构对于级联失效破坏的抵御能力,为物流应急管理提供理论支持。     

耦合级联失效系统可靠性建模与分析

现实生活中绝大多数系统并不是孤立存在的,如通信网和电网,它们相互依存、相互影响,这种系统间的耦合关系使得级联失效范围变得更广,导致级联过程更为复杂,从而影响整个系统可靠性及其正常运行。针对此问题,论文以电力通信系统为研究背景,给出了耦合系统转移率的解析表达,分析了元件负载增加影响元件故障率的级联失效效应和子系统间的相依关系,建立了耦合级联失效系统的可靠性模型,并证明了系统可靠度的计算方法和解析式结果。并且利用一个算例展示了耦合系统发生级联失效的具体过程,以验证该方法的有效性与可行性。本文为基于负载和时间的耦合系统的级联研究提供了新的思路,可拓展至不同的耦合关系、耦合强度以及不同的负载分配模式来进一步研究系统的级联失效过程以及可靠度分析。     

基于Markov更新过程的城市交通网络级联失效评价模型

根据路段单元状态与其功能之间的关系,给出了路段单元状态的‘失效—非失效’二态表示方法,进一步根据网络中路段单元之间的连接关系,提出了道路交通网络‘级联失效’态的定义及识别方法;利用更新理论及Markov链相关理论,分析了道路交通网络级联失效态—非级联失效态持续时间随机变化的概率分布规律,给出了对假想分布的未知参数进行估计及对假想分布进行假设检验的方法,并提出了以失效次数及转移概率为主要评价参数的交通网络级联失效评价模型。以一个实际路网为例,对模型进行了标定,将标定好的模型评价结果与实际观察结果进行了比对,结果显示模型具有较好的实用性。     

基于TOPSIS模型的机场网络节点重要度评估

在机场网络中单个机场节点的失效往往会对其他的节点产生影响,特别是关键节点的失效会波及整个网络.准确客观的识别重要节点机场关乎整个机场网络的安全运营.本文分析了机场网络拓扑特性中的度、集聚系数和接近度指标,考虑了机场旅客吞吐量和所在城市人口等交通经济特性指标,使用熵权法确定权重的基础上,应用TOPSIS法构建综合评价体系模型,最后以华东地区机场网络为例进行节点重要度排序.结果表明与单一指标的评估结果相比,该方法更加全面客观的确定不同属性指标的权重,避免了不同指标取值的差异性,使评价更加全面,更符合机场网络实际运营情况.     

供应链网络可靠性的多层Bayes估计模型

对供应链网络可靠性进行界定和分析,以节点企业间的协同为基础,得到可靠度计算模型,以此为依据采集实证样本无失效运行的数据.根据供应链网络可靠性统计特性,建立一种多层Bayes估计方法,应用于样本可靠性评估中.在估计失效率的基础上,对供应链网络可靠度进行估计,对仿真结果进行分析,显示多层Bayes估计方法应用效果较好,精确度高,反映了参数不确定性对供应链网络可靠性的影响,能够较好地解决依据无失效数据判定供应链网络可靠性水平的问题.     

工程项目组合风险扩散模型的级联失效分析

为构建符合工程项目组合特点的风险扩散模型,解决风险扩散问题。本文考虑风险扩散的双关系载体—项目交互关系和风险因素逻辑关系,构建工程项目组合风险扩散的双层相依网络模型,运用级联失效理论提出风险扩散规则,通过数值仿真分析风险扩散特征。仿真结果发现：工程项目组合中,双层网络模型能够反映风险在项目和风险因素双关系载体中的扩散特征;与单层网络风险扩散模型相比,构建的模型展现出差异性的风险扩散效应,风险扩散在工程项目组合中表现出更剧烈的级联失效过程。风险扩散模型作为工程项目组合风险扩散问题的前置性研究,为进一步风险扩散网络稳定性的研究提供新思路和启发。     

节点动态增长对复杂网络传输效率的影响研究

在真实的复杂网络中,网络节点会因为网络拓扑结构的变化而增减,进而导致网络节点间传输效率降低.针对这一问题,通过分析复杂网络节点的动态变化,提出网络节点增加的动态传输模型,并利用真实复杂网络的数据模拟仿真,研究网络节点变化对网络传输效率的影响.结果表明:网络的初始大小会随网络节点的动态增加而变化,其传输效率受节点动态增加的影响在最初阶段表现明显,随着节点的继续增加,网络传输效率会趋于平稳,表现出稳定的网络特性.在这个过程中,复杂网络每次新加入节点的个数和节点边维持了网络信息传输的信息量,强化了网络传的输性能,使得网络具有较好的总体控制能力和有效的节点连接方式.     

多社团加权复杂网络建模及其级联抗毁性研究

为了研究社团结构和权重因素对网络级联抗毁性的影响,引入节点和边的消亡机制,建立了一类具有社团结构的加权网络模型.采用本方法生成网络的度、强度和边权分布都呈现无标度特性,比现有BBV (Barrat-Barthelemy-Vespignani)模型具有更好的社团结构特性,且幂律指数、模块度参数可调.在此基础上研究了网络的级联抗毁性,采用节点及其邻居节点强度的函数定义网络负荷,故障节点负荷采用"局部定义,局部分配"的策略.仿真分析了边权演化参数、模块度函数、攻击策略和演化时间对网络级联抗毁性的影响.结论表明,网络的抗毁性与边权演化参数、网络演化时间成反比,与模块度的关系不是单调的而是存在一个阈值.优先攻击度最大节点的策略对网络抗毁性破坏最大,且在多节点遭受攻击时,网络的故障规模会发生突变.文章的研究结论对故障的预防与控制以及网络的建设具有一定的参考价值.     

基于改进节点重要度引力模型的航路网拥堵节点识别

航路网络存在一些关键航路点对系统整体具有重要控制作用,而有效辨识这些重要节点对缓解空中交通拥堵,提高航路运行效率具有极大意义.以复杂网络理论为基础,从网络视角结合中心度及节点服务能力通过改进传统引力模型进行节点重要度评估;然后基于改进节点重要度引力模型进行航路网络拥堵节点识别仿真,并将结果与传统介数法进行对比验证.研究表明:改进的引力模型识别的重要节点,不仅具有较大的中心度,且较多位于航路网络流量较大位置;基于引力模型识别航路网络节点重要度的准确率更高,在提高网络通行率基础上更及时地识别航路网络易拥堵节点,对预防节点失效、减少航路网络拥堵具有积极作用.     

基于不确定理论的原油海运网络连通可靠性研究

原油海运网络是原油进口国的海上生命线,为科学衡量网络中节点受到突发事件影响后的原油海运网络的连通可靠性,本文采用不确定变量来描述突发事件发生后各节点的连通性,引入不确定理论对原油海运网络连通可靠性进行评估,并建立了不确定原油海运网络的最可靠路径选择模型。本文不确定变量的引入不再依赖较多的历史数据去描绘节点失效的概率分布,而且提出的最可靠路径选择模型可以确保突发事件发生后原油的及时运输。本文还提出了α-最可靠路径和最大测度最可靠路径选择问题,给出不确定原油海运网络最可靠路径风险值的不确定分布,为突发事件发生后决策者的路径选择提供依据。本文以中国进口原油海运网络为例作案例分析。     

Probabilistic Analysis of Failures in Power Transmission Networks and Phase Transitions: Study Case of a High-Voltage Power Transmission Network

We present the failure analysis of a study case of a high-voltage power transmission network using the mathematical model of cascading blackouts introduced in Carreras et al. (Chaos 12:985–994, 2002). When the load of the network is randomly perturbed, we study the probability density function of the measure of the size of the resulting blackout as a function of the mean load level. The mathematical model used approximates the network with an undirected graph made of generator, load and junction nodes connected by branches representing the lines of the network. The electric flow in the network is found solving the optimal DC power-flow problem and the sequence of events causing a cascading blackout is simulated using a numerical scheme. The analysis points out the existence of values of the mean total power demand such that for higher values when the blackout size measure increases the decay of the blackout size measure probability density function changes from being best fitted by a negative exponential to being best fitted by an inverse power law. The analogies between this phenomenon and the phase transition phenomenon studied in statistical mechanics are discussed. The website: contains some auxiliary material including animations that helps the understanding of this paper. The numerical experience reported in this paper has been obtained using the computing grid of ENEA (Roma, Italy).     

基于失效边数概率分布的K-终端网络重要度计算方法

重要度是现代网络薄弱环节识别的常用工具,其能量化网络不同的边对网络可靠性的影响程度。以往的K-终端网络重要度计算方法需已知网络边的可靠性以及边发生失效相互独立的条件,不能满足现实网络对于网络重要度计算的需求。鉴于此,为了突破这些条件的限制,本文在给定失效边数目的概率分布的背景下,发展K-终端网络重要度的计算方法,并提供一个十二面体网络的算例,验证了该计算方法的有效性和正确性。     

Minimum vertex cover problem for coupled interdependent networks with cascading failures

This paper defines and analyzes a generalization of the classical minimum vertex cover problem to the case of two-layer interdependent networks with cascading node failures that can be caused by two common types of interdependence. Previous studies on interdependent networks mainly addressed the issues of cascading failures from a numerical simulations perspective, whereas this paper proposes an exact optimization-based approach for identifying a minimum-cardinality set of nodes, whose deletion would effectively disable both network layers through cascading failure mechanisms. We analyze the computational complexity and linear 0–1 formulations of the defined problems, as well as prove an LP approximation ratio result that generalizes the well-known 2-approximation for the classical minimum vertex cover problem. In addition, we introduce the concept of a “depth of cascade” (i.e., the maximum possible length of a sequence of cascading failures for a given interdependent network) and show that for any problem instance this parameter can be explicitly derived via a polynomial-time procedure.     

基于可靠性弹性指标的系统弹性度量方法

为深入研究系统弹性问题,首先分析系统中不同节点和边的可靠性弹性指标。通过引入节点弹性与边弹性,并考虑节点弹性与边弹性二者的联系以及对系统弹性的影响,建立了能够反映系统拓扑结构变化的弹性度量方法模型。最后,在对弹性度量方法的验证环节中,引入了具有分层特性的交通系统,按照所述弹性度量方法对分层交通系统中的节点弹性以及边弹性进行了分析,发现该种分层交通系统的整体弹性程度一般,任何小的干扰或者故障都有可能造成该交通系统拥堵或瘫痪。     

生命线网络系统多节点失效的应急抢修队伍派遣模型研究

针对生命线网络系统中多个节点失效的应急抢修问题,给出了抢修队伍派遣优化模型以及模型的求解方法。在本文中,首先考虑应急修复所需时间、各节点失效所造成的损失和应急修复所需成本等因素,构建了以节点失效损失最小和应急修复成本最低为目标的抢修队伍派遣优化模型;然后针对优化模型的特点,给出了模型的求解方法。最后,通过一个算例分析说明了构建的模型的可行性和有效性。     

Percolation of interdependent network of networks

Complex networks appear in almost every aspect of science and technology. Previous work in network theory has focused primarily on analyzing single networks that do not interact with other networks, despite the fact that many real-world networks interact with and depend on each other. Very recently an analytical framework for studying the percolation properties of interacting networks has been introduced. Here we review the analytical framework and the results for percolation laws for a Network Of Networks (NONs) formed by n interdependent random networks. The percolation properties of a network of networks differ greatly from those of single isolated networks. In particular, because the constituent networks of a NON are connected by node dependencies, a NON is subject to cascading failure. When there is strong interdependent coupling between networks, the percolation transition is discontinuous (first-order) phase transition, unlike the well-known continuous second-order transition in single isolated networks. Moreover, although networks with broader degree distributions, e.g., scale-free networks, are more robust when analyzed as single networks, they become more vulnerable in a NON. We also review the effect of space embedding on network vulnerability. It is shown that for spatially embedded networks any finite fraction of dependency nodes will lead to abrupt transition.     

Recent advances on failure and recovery in networks of networks

Until recently, network science has focused on the properties of single isolated networks that do not interact or depend on other networks. However it has now been recognized that many real-networks, such as power grids, transportation systems, and communication infrastructures interact and depend on other networks. Here, we will present a review of the framework developed in recent years for studying the vulnerability and recovery of networks composed of interdependent networks. In interdependent networks, when nodes in one network fail, they cause dependent nodes in other networks to also fail. This is also the case when some nodes, like for example certain people, play a role in two networks, i.e. in a multiplex. Dependency relations may act recursively and can lead to cascades of failures concluding in sudden fragmentation of the system. We review the analytical solutions for the critical threshold and the giant component of a network of n interdependent networks. The general theory and behavior of interdependent networks has many novel features that are not present in classical network theory. Interdependent networks embedded in space are significantly more vulnerable compared to non-embedded networks. In particular, small localized attacks may lead to cascading failures and catastrophic consequences. Finally, when recovery of components is possible, global spontaneous recovery of the networks and hysteresis phenomena occur. The theory developed for this process points to an optimal repairing strategy for a network of networks. Understanding realistic effects present in networks of networks is required in order to move towards determining system vulnerability.     

Minimizing maximum risk for fair network connection with interval data

In this paper we introduce a minimax model for network connection problems with interval parameters. We consider how to connect given nodes in a network with a path or a spanning tree under a given budget, where each link is associated with an interval and can be established at a cost of any value in the interval. The quality of an individual link （or the risk of link failure, etc.） depends on its construction cost and associated interval. To achieve fairness of the network connection, our model aims at the minimization of the maximum risk over all links used. We propose two algorithms that find optimal paths and spanning trees in polynomial time, respectively. The polynomial solvability indicates salient difference between our minimax model and the model of robust deviation criterion for network connection with interval data, which gives rise to NP-hard optimization problems.