Fundamentals of the analytic network process — Dependence and feedback in decision-making with a single network

The Analytic Network Process (ANP) is a multicriteria theory of measurement used to derive relative priority scales of absolute numbers from individual judgments (or from actual measurements normalized to a relative form) that also belong to a fundamental scale of absolute numbers. These judgments represent the relative influence, of one of two elements over the other in a pairwise comparison process on a third element in the system, with respect to an underlying control criterion. Through its supermatrix, whose entries are themselves matrices of column priorities, the ANP synthesizes the outcome of dependence and feedback within and between clusters of elements. The Analytic Hierarchy Process (AHP) with its independence assumptions on upper levels from lower levels and the independence of the elements in a level is a special case of the ANP. The ANP is an essential tool for articulating our understanding of a decision problem. One had to overcome the limitation of linear hierarchic structures and their mathematical consequences. This part on the ANP summarizes and illustrates the basic concepts of the ANP and shows how informed intuitive judgments can lead to real life answers that are matched by actual measurements in the real world (for example, relative dollar values) as illustrated in market share examples that rely on judgments and not on numerical data. Thomas L. Saaty holds the Chair of University Professor, Katz Graduate School of Business, University of Pittsburgh, Pittsburgh, PA, and obtained his Ph.D. in mathematics from Yale University. Before that he was a professor at the Wharton School of the University of Pennsylvania for ten years. Prior to that he spent seven years at the Arms Control and Disarmament Agency in the State Department in Washington, DC, that carried out the arms reduction negotiations with the Soviets in Geneva. His current research interests include decision-making, planning, conflict resolution and synthesis in the brain. As a result of his search for an effective means to deal with weapons tradeoffs at the Disarmament Agency and, more generally, with decision-making and resource allocation, Professor Saaty developed The Analytic Hierarchy Process (AHP) and its generalization to dependence and feedback, the Analytic Network Process (ANP). He is co-developer of the software Expert Choice and of the software Super Decisions for decisions with dependence and feedback. He has authored or co-authored twelve books on the AHP/ANP. Professor Saaty has also written a number of other books that embrace a variety of topics, including Modern Nonlinear Equations, Nonlinear Mathematics, Graph Theory, The Four Color Problem, Behavioral Mathematics, Queuing Theory, Optimization in Integers, Embracing the Future and The Brain: Unraveling the Mystery of How It Works. His most recent book is Creative Thinking, Problem Solving & Decision Making. The book is a rich collection of ideas, incorporating research by a growing body of researchers and practitioners, profiles of creative people, projects and products, theory, philosophy, physics and metaphysics...all explained with a liberal dose of humor. He has published more than 300 refereed articles in a wide variety of professional journals. He has been on the editorial boards of Mathematical Reviews, Operations Research, Naval Research Logistics Quarterly, Mathematical and Computer Modeling, Socio-Economic Planning Sciences, Applied Mathematics Letters, and several others. He also served as consultant to many corporations and governments.     

一种基于流量工程的网络端到端性能分析算法

网络性能分析与优化是面向流量工程网络设计与管理的关键任务之一。以流量工程为基础,应用网络图的方法描述网络拓扑,通过对链路性能参数描述矩阵的标准化变换及网络邻接关联矩阵传递闭包的求解,同时结合网络事件的随机性,给出一种求解网络链路数据传输能力、分析网络端到端连通性能的算法,为网络设计及其性能分析提供了一种便捷可行的方法。     

基于耦合自抗扰控制器的无标定手眼协调

研究机械臂在手眼关系未知情况下依靠视觉信息引导完成精确定位及跟踪问题。基于耦合自抗扰控制器原理,设计了不依赖于特定任务的广泛意义下的手眼协调控制器。通过将全局固定眼和局部手上眼相结合,实现了整个机器人操作空间范围内的精确定位与跟踪。仿真和实验验证了这一方法的可行性和有效性。     

中小企业网络组织的规模经济分析

中小企业生存和发展的特点决定其网络组织具有整体目的长期化，企业功能分布式集成，项目导向的构想和实施的即时化等特点,由于信息技术和制造技术的进步，中小企业可通过适合的网络组织整合和利用外资源，取得大企业同样的规模经济效益，弥补其由于规模小而带来的市场，技术创新，抵抗风险和复杂任务解决等能力的不足。     

基于MATLAB的神经网络在股市预测中的应用

以道氏三大假说作为理论基础，设计一个三层BP网络，并建立相应的数学模型，以MATLAB为工具，个股上海石化(600688)140天实际收盘价作为样本，对网络进行训练后，预剩10天的收盘价，并计算出与实际收盘价的高差Q＝0．0146，Q已经小到几乎可以忽视的程度。     

考虑施工次序与土质问题的土石方调运的网络模型研究

土石方施工在高速公路建设中数量巨大，传统的人工调配土石方方法既费时又无法得到最优调运方案．在现有的研究基础上提出考虑施工次序与土质问题的土石方调运研究的网络模型。     

基于RBF的机械手建模误差补偿自适应控制

针对机械手动力学建模误差,提出了基于RBF神经网络误差补偿的自适应控制策略。在基于逆动力学的计算力矩控制方法的基础上,对系统输入与目标轨迹进行修正,设计了两种误差补偿自适应控制器。利用RBF神经网络对修正项在线自学习,并根据Lyapunov稳定性理论建立了网络权重自适应学习律,保证了跟踪误差的收敛及系统的稳定。以平面转动双臂机械手轨迹跟踪为例进行仿真,结果表明该方法能够有效地补偿建模误差,提高了系统的控制性能并使控制系统具有对参数摄动的鲁棒性,对于机械手自适应控制具有一定的可行性。     

引入生态修复技术的太湖流域生态补偿方案

针对生物膜法、活性污泥法等适用于点源污染治理的技术无法有效解决面源污染的问题,引入生态修复技术,选取美人蕉作为修复植物,构建了太湖流域污染治理生态补偿模型。并以2005年太湖流域COD削减为例进行分析,结果显示:通过生态补偿方案激励太湖流域苏浙沪各地区合作治污可降低流域治理成本约5%,引入生态修复技术可进一步降低合作治污成本约12%;引入生态修复技术后,为促进苏浙沪各地区合作治污,提升整个流域的治理效率,应建立流域地区间生态补偿机制,太湖流域实证研究确定了地区之间的补偿标准:浙江省对江苏省、上海市的COD生态补偿价格为6648.30元/吨、8164.21元/吨。     

D-FNN模型对中国FDI的预测

建立了动态模糊神经网络模型,并运用此模型对中国经济产生深远影响的FDI进行了预测。结果表明D-FNN在预测精度上表现优异,具有一定的实用性。     

点与线的复制：基于网络思维的系统观

＂复制＂是一种普遍存在的现象,其表现为重复、拷贝或再造某种事物、结构或关系。这种现象在生命系统中尤为明显。通过把系统表征为由点（属性）和线（关系）所组成的网络,网络思维可以作为考察各种系统的认知工具。这种思维除了可以进行诸如还原、切出、背景化和层级化等多种表层操作以外,还具有更深层的点和线的复制。以对部分与整体、系统和环境的辨析为引导,本文首先简要回顾了鲁曼系统理论中的系统观发展史,然后以现有系统观的生命系统模式作为框架,提出把复制性作为网络思维的图式（基于点线符号的网络）及其考察的对象（系统）的基本特性,从而为利用网络思维考察各种系统提供新的理论依据和分析视角。