基于Petri网的微博网络信息传播模型

微博网络中的信息传播模型是分析用户行为,找出传播路径,确定领袖人物,发现舆情热点等研究的基础。虽然多种不同角度的信息传播模型已经得到广泛研究,但缺乏对信息动态传播过程的直观描述。本文基于Petri网的结构和特征,针对微博网络信息传播过程,提出了一种简单直观的描述模型,该模型首先对微博网络的信息动态传播过程中的对象进行结构化描述。本文根据微博网络的用户结构关系,并利用Petri网的相关理论,形式化解释和定义信息传播基本对象,从而更加直接描述了微博网络中的转发、评论、回复等多种用户行为。在此基础上,本文利用Petri网能够描述信息流动问题的特征,结合颜色Petri网和时延Petri网,从Petri网系统的角度表示信息动态传播路径,并研究网络的动态性质和传播条件,使得信息传播模型更加真实地模拟信息传播情况。最后本文分析信息传播算例和新浪微博真实数据实验,验证了模型的有效性和可行性,为舆情态势分析以及用户行为的研究提供帮助和支持,同时也为其它社交网络信息传播的用户行为描述提供了新的思路。     

A Simulated Annealing Approach to Communication Network Design

This paper explores the use of the meta-heuristic search algorithm Simulated Annealing for solving a minimum cost network synthesis problem. This problem is a common one in the design of telecommunication networks. The formulation we use models a number of practical problems with hop-limit, degree and capacity constraints. Emphasis is placed on a new approach that uses a knapsack polytope to select amongst a number of pre-computed traffic routes in order to synthesise the network. The advantage of this approach is that a subset of the best routes can be used instead of the whole set, thereby making the process of designing large networks practicable. Using simulated annealing, we solve moderately large networks (up to 30 nodes) efficiently.     

电信社群网络用户行为特征及演化分析

通过某地移动客户的通话数据构建电信社群网络,并对其网络结构进行分析,发现电信社群网络并不满足小世界特征,而且该网络的演化是以边生长为主导。基于该结构特征,构建电信社群网的演化模型,发现网络非均匀性与节点的朋友圈数目、连接概率和新增节点边数有关。其研究结论对新运营商通过营销策略的制定,推动电信社群网络快速向小世界网络演化具有积极的现实意义。     

Optimization of Cascade‐Resilient Electrical Infrastructures and its Validation by Power Flow Modeling

Large‐scale outages on real‐world critical infrastructures, although infrequent, are increasingly disastrous to our society. In this article, we are primarily concerned with power transmission networks and we consider the problem of allocation of generation to distributors by rewiring links under the objectives of maximizing network resilience to cascading failure and minimizing investment costs. The combinatorial multiobjective optimization is carried out by a nondominated sorting binary differential evolution (NSBDE) algorithm. For each generators–distributors connection pattern considered in the NSBDE search, a computationally cheap, topological model of failure cascading in a complex network (named the Motter‐Lai [ML] model) is used to simulate and quantify network resilience to cascading failures initiated by targeted attacks. The results on the 400 kV French power transmission network case study show that the proposed method allows us to identify optimal patterns of generators–distributors connection that improve cascading resilience at an acceptable cost. To verify the realistic character of the results obtained by the NSBDE with the embedded ML topological model, a more realistic but also more computationally expensive model of cascading failures is adopted, based on optimal power flow (namely, the ORNL‐Pserc‐Alaska) model). The consistent results between the two models provide impetus for the use of topological, complex network theory models for analysis and optimization of large infrastructures against cascading failure with the advantages of simplicity, scalability, and low computational cost.     

Integrating Social Network Effects in the Share‐Of‐Choice Problem

Accounting for social network effects in marketing strategies has become an important issue. Taking a step back, we seek to incorporate and analyze social network effects on new product development and then propose a model to engineer product diffusion over a social network. We build upon the share‐of‐choice (SOC) problem, which is a strategic combinatorial optimization problem used commonly as one of the methods to analyze conjoint analysis data by marketers in order to identify a product with largest market share, and show how to incorporate social network effects in the SOC problem. We construct a genetic algorithm to solve this computationally challenging (NP‐Hard) problem and show that ignoring social network effects in the design phase results in a significantly lower market share for a product. In this setting, we introduce the secondary operational problem of determining the least expensive way of influencing individuals and strengthening product diffusion over a social network. This secondary problem is of independent interest, as it addresses contagion models and the issue of intervening in diffusion over a social network, which are of significant interest in marketing and epidemiological settings.     

Axiomatic Based Decomposition for Conceptual Product Design

This paper describes a structured methodology for decomposing the conceptual design problem in order to facilitate the design process and result in improved conceptual designs that better satisfy the original customer requirements. The axiomatic decomposition for conceptual design method combines Alexander's network partitioning formulation of the design problem with Suh's Independence Axiom. The axiomatic decomposition method uses a cross‐domain approach in a House of Quality context to estimate the interactions among the functional requirements that are derived from a qualitative assessment of customer requirements. These interactions are used in several objective functions that serve as criteria for decomposing the design network. A new network partitioning algorithm is effective in creating partitions that maximize the within‐partition interactions and minimize the between‐partition interactions with appropriate weightings. The viability, usability, and value of the axiomatic decomposition method were examined through analytic comparisons and qualitative assessments of its application. The new method was examined using students in engineering design capstone courses and it was found to be useable and did produce better product designs that met the customer requirements. The student‐based assessment revealed that the process would be more effective with individuals having design experience. In a subsequent assessment with practicing industrial designers, it was found that the new method did facilitate the development of better designs. An important observation was the need for limits on partition size (maximum of four functional requirements.) Another issue identified for future research was the need for a means to identify the appropriate starting partition for initiating the design.     

Mechanism Design With Renegotiation and Costly Messages

According to standard theory, the set of implementable efficient outcome functions is greatly reduced if the mechanism or contract can be renegotiated ex post. In some cases, contracts can achieve nothing and so, for example, the hold‐up problem may be severe. This paper shows that if the mechanism is designed in such a way that sending a message involves a small cost, then renegotiation essentially does not restrict the set of efficient implementable functions. Given a weak preference‐reversal condition, any Pareto‐efficient, bounded social choice function can be implemented in subgame‐perfect equilibrium in a renegotiation‐proof manner, for any strictly positive message cost. The key point is that messages themselves can act as punishments.     

Reliability evaluation of a multicast over coded packet networks

Network coding is a generalization of conventional routing methods that allows a network node to code information flows before forwarding them. While it has been theoretically proved that network coding can achieve maximum network throughput, theoretical results usually do not consider the stochastic nature in information processing and transmission, especially when the capacity of each arc becomes stochastic due to failure, attacks, or maintenance. Hence, the reliability measurement of network coding becomes an important issue to evaluate the performance of the network under various system settings. In this paper, we present analytical expressions to measure the reliability of multicast communications in coded networks, where network coding is most promising. We define the probability that a multicast rate can be transmitted through a coded packet network under a total transmission cost constraint as the reliability metric. To do this, we first introduce an exact mathematical formulation to construct multicast connections over coded packet networks under a limited transmission cost. We then propose an algorithm based on minimal paths to calculate the reliability measurement of multicast connections and analyze the complexity of the algorithm. Our results show that the reliability of multicast routing with network coding improved significantly compared to the case of multicast routing without network coding.     

企业信用内生网络模型及其演化研究

本文考虑上游企业和下游企业两个部门，通过构建企业内生网络模型研究企业间信用关联内在形成机制及其演化特征。通过对内生网络模型仿真研究，结果表明本文构建的模型重现了现实企业系统存在的一些特征：企业信用网络度分布服从幂律分布，该网络具有无标度特征；较长的合并周期则能更好地反映企业间信用关系，且随着合并周期变大，网络密度也显著增大；企业资产规模分布具有幂律尾部特征，企业资产增长率随时间演化逐渐呈收敛状，且其概率分布近似于正态分布。     

The ties that lead: A social network approach to leadership

This article investigates, for leadership research, the implications of new directions in social network theory that emphasize networks as both cognitive structures in the minds of organizational members and opportunity structures that facilitate and constrain action. We introduce the four core ideas at the heart of the network research program: the importance of relations, actors' embeddedness, the social utility of connections, and the structural patterning of social life. Then we present a theoretical model of how network cognitions in the minds of leaders affect three types of networks: the direct ties surrounding leaders, the pattern of direct and indirect ties within which leaders are embedded in the whole organization and the interorganizational linkages formed by leaders as representatives of organizations. We suggest that these patterns of ties can contribute to leader effectiveness.     

社交网络、 投资者关注与股价同步性

随着以微博、微信为代表的社交网络信息平台在中国的崛起,形成了新媒体时代下信息资讯生成与扩散的完整传播链条,深刻地影响着金融市场参与主体的学习认知习惯、投资决策理念、交易行为模式,最终影响不同金融资产的价格波动规律.本文在新媒体时代情景下,以社交网络信息披露与传播平台为切入点,基于信息关注度、信赖度、更新频率等三层维度,构建社交网络微博信息质量指标体系,研究社交网络信息质量与股价同步性的内在关联关系.研究表明:微博信息质量与股价同步性有着显著的高度负向线性关联性,并且呈现出非线性U型关系.即随着社交网络信息质量水平的提升,股价同步性逐渐降低到达最小值,而后又逐渐提高.研究结论为证明上市公司社交网络微博平台对股价同步性有较强影响力,提供了中国金融市场的证据.     

在线社交网络虚假信息交互量最小化的边阻断策略研究

在线社交媒体的蓬勃发展改变了人们获取信息的模式,大量的信息通过社交平台传播,信息内容的真实性把关弱化,各类虚假信息依托社交媒体野蛮生长,网络空间治理,培育健康的网络生态意义重大。本文通过最小化用户之间的虚假信息交互量,研究社交网络中虚假信息传播路径的阻断策略。给定在线社交网络G=（V,E,P,H）,H表示用户之间信息交互量,已知虚假信息传播源集合S⊆V,虚假信息交互量最小化问题是从E中选取哪K条边,使得这些边被阻断之后,虚假信息在用户之间的交互总量最小。首先证明了该问题是NP-困难的,进而证明了问题的目标函数计算是#P-困难。其次,证明了该问题目标函数既不是次模函数也不是超模函数。再次,提出了两阶段贪婪算法（TSGA）来解决该问题,即先获取候选集合E^sa,然后选取阻断集合E'。最后,通过实际在线社交网络数据对模型和算法的有效性进行了分析,实验表明本文提出的算法比现有算法更加有效。     

具有边权特性的社会网络重要成员识别

根据成员间关系的强弱给社会网络中各边赋予权重,将二元网络扩展到边权网络,提出一种新的度量指标。该指标通过累加一个成员在网络中成为关键点的次数来度量其删除后给整个网络带来的损害程度,从而判断该成员对维护网络运行绩效的重要性。通过组织沟通网络的实例分析,说明新指标可以从维护网络安全的视角,有效辨识那些虽然结构位置不显著,但对网络安全具有重大隐患的重要成员。     

管理越位现象:医患群体性事件社会网络的稳定性与效率

医患冲突问题成为当前社会热点问题之一。医患群体性事件当事者的社会网络结构呈现出越级上访、参与者个体的异质性、存在转移支付和动态递减的连接成本等复杂特征。在经典的社会网络JW模型上考虑上述社会网络特征,构建了修正的RJW(Revised Jackson-Wolinsky Model)社会网络模型。运用穷举搜索法,研究了医患冲突社会网络结构的稳定性和效率。结合南平医闹事件的案例分析,研究结果表明,当直接连接成本和连接收益较低时,星形社会网络稳定且高效;随着连接收益的上升,同时满足稳定性和有效的社会网络结构呈现出多种间接连接形态。该社会网络连接模型揭示了突发事件应急管理中“越位”、“越权”现象的产生条件:其关键因素是连接收益和连接成本的权衡。     

广州软件产业社会网络与竞争关系复杂网络的分析与比较

通过对广州软件产业的问卷调查,建立了61个公司的CEO自我中心社会网络、2个公司的衍生网络以及578个公司的基于产品的竞争关系网络模型,并分别采用社会网络分析方法、复杂网络分析方法对上述模型进行了分析与比较。发现了广州软件产业CEO自我中心社会网络具有较强的封闭性,竞争关系复杂网络具有幂律分布、小世界性等特点,以及该产业的公司衍生网络与竞争关系复杂网络之间的内在联系。     

Bounds of Relative Regret Limit in p‐Robust Supply Chain Network Design

This research studies the p‐robust supply chain network design with uncertain demand and cost scenarios. The optimal design integrates the supplier selection together with the facility location and capacity problem. We provide a new framework to obtain the relative regret limit, which is critical in the robust supply chain design but is assumed to be a known value in the existing literature. We obtain lower and upper bounds for relative regret limit and obtain a sequence of optimal solutions for series relative regret limits between the upper and lower bounds. An algorithm for p‐robust supply chain network design is provided. A series of numerical examples are designed to find the properties of the bottleneck scenarios. A scenario with low probability and a low optimal objective function value for the scenario has a greater chance of being a bottleneck. To focus only on the influence from the relative regret, we also introduce three separate new objective functions in p‐robust design. The proposed new theories and approaches provide a sequence of options for decision makers to reduce the marketing risks effectively in supply chain network design.     

多级供应链系统成本分析随机网络模型及算法研究

供应链成本管理是企业战略管理的核心组成部分。为研究多级供应链网络系统的成本组成及其分布特征、分析各节点企业的成本管理对多级供应链网络系统的影响、找到供应链系统成本管理中的薄弱环节和关键企业,本文构建了多级供应链系统成本的随机网络分析模型。首先研究了模型的结构性质特征,给出成本分布特征的解析算法。然后扩展模型,分别从系统成本类型构成(生产成本、库存成本和物流成本)和系统对企业成本波动的灵敏度两个角度深入研究多级供应链网络成本问题。数值算例分析结果说明了多级供应链网络系统成本分析模型和相关算法的有效性和实用性。     

Telecommunications Network Design—Comparison of Alternative Approaches

The design and development of the network infrastructure to support mission‐critical applications has become a critical and‐complex activity. This study explores the use of genetic algorithms (GA) for network design in the context of degree‐constrained minimal spanning tree (DCMST) problem; compares for small networks the performance of GA with a mathematical model that provides optimal solutions; and for larger networks, compares GA's performance with two heuristic methods—edge exchange and primal algorithm. Two performance measures, solution quality and computation time, are used for evaluation. The algorithms are evaluated on a wide variety of network sizes with both static and dynamic degree constraints on the network nodes. The results indicate that GA provides optimal solutions for small networks. For larger networks it provides better solution quality compared to edge exchange and primal method, but is worse than the two methods in computation time.     

Minimum cost network design in strategic alliances

Strategic alliances are established between firms to improve their competitiveness in markets and generally appear in the form of joint ventures. Such collaborative efforts require centralized planning, and the survival of the alliance largely depends on the success of joint planning processes. In this regard, we investigate the opportunities that centralized collaboration can offer to firms when designing their service networks. Apart from the classical fixed and variable costs associated with the network design, we also consider transaction costs induced by the formation of the alliance, which can broadly be defined as cost components related to the coordination and monitoring of the people, efforts and resources. We concentrate on bilateral alliances and develop alternative models for solving their associated network design problem. We also adopt a state-of-the-art heuristic to solve large-scale instances. Our findings confirm that accounting for the transaction cost in network design is vital for the alliance. These transaction costs can be high enough to even render the collaboration unattractive. Hence, careful data collection and model treatment are required before deciding whether to form an alliance.