Tractable Approximations to Robust Conic Optimization Problems

In earlier proposals, the robust counterpart of conic optimization problems exhibits a lateral increase in complexity, i.e., robust linear programming problems (LPs) become second order cone problems (SOCPs), robust SOCPs become semidefinite programming problems (SDPs), and robust SDPs become NP-hard. We propose a relaxed robust counterpart for general conic optimization problems that (a) preserves the computational tractability of the nominal problem; specifically the robust conic optimization problem retains its original structure, i.e., robust LPs remain LPs, robust SOCPs remain SOCPs and robust SDPs remain SDPs, and (b) allows us to provide a guarantee on the probability that the robust solution is feasible when the uncertain coefficients obey independent and identically distributed normal distributions. The research of the author was partially supported by the Singapore-MIT alliance. The research of the author is supported by NUS academic research grant R-314-000-066-122 and the Singapore-MIT alliance.     

Computational Sensitivity Analysis for State Constrained Optimal Control Problems

A theoretical sensitivity analysis for parametric optimal control problems subject to pure state constraints has recently been elaborated in [7,8]. The articles consider both first and higher order state constraints and develop conditions for solution differentiability of optimal solutions with respect to parameters. In this paper, we treat the numerical aspects of computing sensitivity differentials via appropriate boundary value problems. In particular, numerical methods are proposed that allow to verify all assumptions underlying solution differentiability. Three numerical examples with state constraints of order one, two and four are discussed in detail.     

向量优化中的二阶灵敏性分析

借助二阶相依导数的概念,研究了向量优化问题中扰动映射的二阶灵敏性.     

Parametric Sensitivity Analysis of Perturbed PDE Optimal Control Problems with State and Control Constraints

We study parametric optimal control problems governed by a system of time-dependent partial differential equations (PDE) and subject to additional control and state constraints. An approach is presented to compute the optimal control functions and the so-called sensitivity differentials of the optimal solution with respect to perturbations. This information plays an important role in the analysis of optimal solutions as well as in real-time optimal control.The method of lines is used to transform the perturbed PDE system into a large system of ordinary differential equations. A subsequent discretization then transcribes parametric ODE optimal control problems into perturbed nonlinear programming problems (NLP), which can be solved efficiently by SQP methods.Second-order sufficient conditions can be checked numerically and we propose to apply an NLP-based approach for the robust computation of the sensitivity differentials of the optimal solutions with respect to the perturbation parameters. The numerical method is illustrated by the optimal control and sensitivity analysis of the Burgers equation.Communicated by H. J. Pesch     

形状优化的全解析敏度分析

在形状优化设计中,建立了边界元的全解析敏度分析技术,并将该技术与通用的形状优化设计算法相结合,对二维平面应力下的弹性体进行形状优化。在优化该文的例题时,用加权求和法处理该例题的多目标问题,最后获得满意的结果。     

Sensitivity analysis in distributed-parameter mechanical system optimization

A class of distributed-parameter optimal design problems is treated, in which the design variable appears as a coefficient in a partial differential operator. Formal sensitivity analysis techniques that are in common use in the engineering literature are studied and made technically precise. Operator theoretic techniques and Frechet differentiation theory are employed to develop a rigorous sensitivity analysis for static and vibrating elastic structures. Two examples involving fourth-order ordinary and partial differential operators, commonly encountered in treating beam and plate elements, are analyzed.     

关于集值映射的相依导数与多目标最优化问题的灵敏度分析

本文在序锥P具有弱紧基的条件下讨论了集值映射F的切导数与F P的切导数之间的关系；引进了集值映射的新的上半局部Lipschitz概念，利用这个概念，我们在有限维空间中给出了多目标最优化问题的灵敏度分析的一个新的结果.     

参数变分不等式的灵敏性分析

本文在所给函数和映射均不可微的前提下，通过建立参数变分不等式和参数Wiener-Hopf方程的等价性，分析了Hilbert空间中参数变分不等式的局部唯一解的灵敏性。文中所用方法是N.D.Yen之方法的改进，使用这一方法可大大简化N.D.Yen一文中主要结果（引理2.1)的证明。     

AHP中判断矩阵排充的灵敏度分析

对AHP中判断矩阵排序的行知归一化方法进行了灵敏度分析,给出了在某个准则下,任意两个方案排序位置不变的情况下判断矩阵中各个元素变化范围的计算公式,所给出的公式直接简单,对于进一步分析判断矩阵权重的稳定性具有重要意义。     

上层带扰动参数的二层多目标优化问题的灵敏度分析

借助集值优化问题的灵敏度分析，讨论了下层无扰动，上层带扰动参数的二层多目标最优化问题的灵敏度分析．     

广义多值拟变分包含的灵敏性分析

借助隐预解算子技巧来研究广义多值拟变分包含的灵敏性分析．所得结果改进、推广和统一了文献中的一些结果．     

Perturbation Approach to Sensitivity Analysis in Mathematical Programming

This paper presents a perturbation approach for performing sensitivity analysis of mathematical programming problems. Contrary to standard methods, the active constraints are not assumed to remain active if the problem data are perturbed, nor the partial derivatives are assumed to exist. In other words, all the elements, variables, parameters, Karush–Kuhn–Tucker multipliers, and objective function values may vary provided that optimality is maintained and the general structure of a feasible perturbation (which is a polyhedral cone) is obtained. This allows determining: (a) the local sensitivities, (b) whether or not partial derivatives exist, and (c) if the directional derivative for a given direction exists. A method for the simultaneous obtention of the sensitivities of the objective function optimal value and the primal and dual variable values with respect to data is given. Three examples illustrate the concepts presented and the proposed methodology. Finally, some relevant conclusions are drawn. The authors are indebted to the Ministry of Science and Education of Spain, Projects CICYT DPI2002-04172-C04-02 and CICYT DPI2003-01362, and to the Fulbright Commission for partial support. The authors are grateful to the referees for comments improving the quality of the paper.     

Optimal Control of Constrained Piecewise Affine Discrete-Time Systems

This paper makes two contributions; firstly, it provides a characterization of the solution of the optimal control problem for piecewise affine discrete-time systems with a quadratic cost function (the generally preferred option) and, secondly, provides a simple method (reverse transformation) for solving this and the previously solved &ell problem. The characterization is useful for on-line implementation.     

基于投影寻踪和最优分割的企业信用评级模型

提出一种基于投影寻踪和最优分割的企业信用评级模型。该模型运用投影寻踪对样本企业进行信用综合评分,将信用综合得分由大到小排序,生成有序样品序列;利用最优分割法对有序样品进行聚类,得出明确的聚类结果;将最优分割点对应的信用综合得分作为划分信用等级的阈值,从而实现对样本企业的信用评级。应用实例证明了该模型的可行性和有效性。     

Active Constraint Set Invariancy Sensitivity Analysis in Linear Optimization

Active constraint set invariancy sensitivity analysis is concerned with finding the range of parameter variation so that the perturbed problem has still an optimal solution with the same support set that the given optimal solution of the unperturbed problem has. However, in an optimization problem with inequality constraints, active constraint set invariancy sensitivity analysis aims to find the range of parameter variation, where the active constraints in a given optimal solution remains invariant.For the sake of simplicity, we consider the primal problem in standard form and consequently its dual may have an optimal solution with some active constraints. In this paper, the following question is answered: “what is the range of the parameter, where for each parameter value in this range, a dual optimal solution exists with exactly the same set of positive slack variables as for the current dual optimal solution?”. The differences of the results between the linear and convex quadratic optimization problems are highlighted too.     

证券投资组合优化问题的强健性的锥优化方法(英文)

本文研究了具有强健性的证券投资组合优化问题.模型以最差条件在值风险为风险度量方法,并且考虑了交易费用对收益的影响.当投资组合的收益率概率分布不能准确确定但是在有界的区间内,尤其是在箱型区间结构和椭球区域结构内时,我们可以把具有强健性的证券投资组合优化问题的模型分别转化成线性规划和二阶锥规划形式.最后,我们用一个真实市场数据的算例来验证此方法.     

Sensitivity Analysis Based Method for Optimal Road Network Pricing

Road pricing is an important economic measure for optimal management of transportation networks. The optimization objectives can be the total travel time or total cost incurred by all the travelers, or some other environmental objective such as minimum emission of dioxide, an so on. Suppose a certain toll is posed on some link on the network, this will give an impact on flows over the whole network and brings about a new equilibrium state. An equilibrium state is a state of traffic network at which no traveler could decrease the perceived travel cost by unilaterally changing the route. The aim of the toll setting is to achieve such an equilibrium state that a certain objective function is optimized. The problem can be formulated as a mathematical program with equilibrium constraints (MPEC). A key step for solving such a MPEC problem is the sensitivity analysis of traffic flows with respect to the change of link characteristics such as the toll prices. In this paper a sensitivity analysis based method is proposed for solving optimal road pricing problems.     

不等式约束的向量优化中值映射的余切上图导数

考虑如下的参数向量优化问题minK{f(w,x)|x∈X,g(w,x)∈C},这里f:W×X→Y是从赋范空间W和X的积到另一个赋范空间Y的Hadamard可微的单值映射,K Y是一个尖闭凸锥,C是Banach空间Z中的一个尖闭凸锥,g:W×X→Z是一个Fréchet可微的映射.借助目标函数的导数、约束映射的余切导数及拉格朗日映射给出了值映射的余切上图导数的两个表示.     

光线寻优算法的寻优机理分析

Based on Fermat’s principle and the automatic optimization mechanism in the propagation process of light,an optimal searching algorithm named light ray optimization is presented,where the laws of refraction and reflection of light rays are integrated into searching process of optimization.In this algorithm,coordinate space is assumed to be the space that is full of media with different refractivities,then the space is divided by grids,and finally the searching path is assumed to be the propagation path of light rays.With the law of refraction,the search direction is deflected to the direction that makes the value of objective function decrease.With the law of reflection,the search direction is changed,which makes the search continue when it cannot keep going with refraction.Only the function values of objective problems are used and there is no artificial rule in light ray optimization,so it is simple and easy to realize.Theoretical analysis and the results of numerical experiments show that the algorithm is feasible and effective.     

一类锥模型非单调信赖域算法及收敛性分析

本文对无约束优化问题提出了一类基于锥模型的非单调信赖域算法.二次模型非单调信赖域算法是新算法的特例.在适当的条件下,证明了算法的全局收敛性及Q-二次收敛性.