Newton type methods for solving nonsmooth equations

1.INTRODUCTION Thenonsmoothequationsproblemplaysanimportant roleinengineering,systemanalysis,management scienceandetc.Manypublicationsdealtwiththe methodsforsolutionofnonsmoothequations,see Refs.[1～4].Letusconsiderthesystemofnons moothequations F(x)=0(1)whereF∶Rn→RmislocallyLipschitzian.NewtonmethodsforsolvingthenonsmoothEq.(1)aregiven asfollows xk+1=xk-V-1kF(xk)(2)whereVkisanelementofvarioussubdifferentialsof Fatxk,forinstance,Clarkesubdifferential[1],B differential[2],b differen…     

Nonsmooth Equations of K-T Systems for a Constrained Minimax Problem

1 .INTRODUCTIONTheconstrainedminimaxproblemplaysanimportantroleinoptimizationsinceithasmanyapplicationsinengineering,systemanalysis,managementscienceandsoon .Therearemanypublicationsdealingwiththisproblem .Inthepresentpaper,weintendtoex plorethenonsmoothequationapproachtosolvetheconstrainedminimaxproblem (P2 )below .Thatis,wefirsttransformthisproblemintoanequivalentsystemofthenonsmoothequation ,thenusegeneral izedNewtonmethodstosolvethenonsmoothequa tion .Wenowconsiderthenonlinear progra…     

非光滑两级优化问题的必要条件及其算法

利用集值分析、非光滑分析与优化理论,研究了两级优化问题的性质、结构,提出了处理这类问题的一个通用性结构化模型,并利用该模型导出了非凸非光滑条件下两级优化问题的微分包含型必要条件,最后给出了其求解的算法及算例．     

具有多值映射的两级优化问题的广义算法研究

两级优化问题是一种非凸非光滑问题，绝大多数问题的求解都是建立在下层有唯一解的基础之上的。而本文针对多值映射，即下层非唯一解的情形，利用隐函数理论，将两级优化问题转化为带有隐函数的非光滑问题，提出求解这类问题的广义算法框架，并证明其收敛性，最后通过实例验证该方法的实用性．     

递阶多目标非光滑优化问题的最优性条件

建立了递阶多目标非光滑优化问题的一个通用性结构化模型,利用参数规划、集值分析及非光滑非线性分析的理论和方法,研究了模型锥有效解存在的最优必要条件和充分条件．     

具有主从结构的非光滑两层优化问题

本文研究一类具有主从结构的非光滑两层化问题。基于Ｃｌａｒｋｅ意义下的非光滑分析理论，给出了该类问题的最优性条件，并对模型的求解方法进行了讨论。     

Distributed Algorithm for Robust Resource Allocation with Polyhedral Uncertain Allocation Parameters

This paper studies a distributed robust resource allocation problem with nonsmooth objective functions under polyhedral uncertain allocation parameters. In the considered distributed robust resource allocation problem, the (nonsmooth) objective function is a sum of local convex objective functions assigned to agents in a multi-agent network. Each agent has a private feasible set and decides a local variable, and all the local variables are coupled with a global affine inequality constraint, which is subject to polyhedral uncertain parameters. With the duality theory of convex optimization, the authors derive a robust counterpart of the robust resource allocation problem. Based on the robust counterpart, the authors propose a novel distributed continuous-time algorithm, in which each agent only knows its local objective function, local uncertainty parameter, local constraint set, and its neighbors’ information. Using the stability theory of differential inclusions, the authors show that the algorithm is able to find the optimal solution under some mild conditions. Finally, the authors give an example to illustrate the efficacy of the proposed algorithm.     

罚函数法在向量似变分不等式中的应用

应用距离函数作为罚函数,建立了向量似变分不等式与向量罚优化问题之间的关系,得到了非光滑向量似变分不等式解的必要和充分条件.讨论了一些具体情况下的相应结果.     

GSVM优化问题的一种新的光滑函数法

提出求解广义支撑向量机(GSVM)优化问题的一种新的光滑函数法,克服了已有算法收敛速度慢且计算结构复杂的缺陷。首先利用最优化理论的KKT互补条件,将GSVM转化为无约束优化问题,然后给出了基于Newton型迭代的光滑函数的迭代方法。给出了这种光滑函数的有关性质、迭代算法的迭代格式及其收敛性。通过理论分析及数值实验证明了该算法对初始点不敏感,且收敛速度快、数值稳定。从而验证了算法的可行性和有效性。     

飞行器耦合系统的一种逐步逼近优化设计方法

阐述了飞行器耦合系统优化设计所面临的计算问题,包括计算量大,计算精度低等.分析指出了产生这些问题的原因在于计算中存在两重嵌套的循环.在上述分析基础上,提出逐步逼近的优化设计方法,在该方法中构造了一个非耦合的近似模型,并针对该近似模型进行优化计算,这样做将嵌套的两个循环过程转化为序列进行的两个循环过程.同时为了在保证精度的前提下提高计算效率,构建了一种近似模型逐步逼近真实模型的迭代格式.仿真算例表明了本方法的有效性.     

Sufficiency and duality for nonsmooth multiobjective programming problems involving generalized univex functions

In this paper, nonsmooth univex, nonsmooth quasiunivex, and nonsmooth pseudounivex functions are introduced. By utilizing these new concepts, sufficient optimality conditions for a weakly efficient solution of the nonsmooth multiobjective programming problem are established. Weak and strong duality theorems axe also derived for Mond-Weir type multiobjective dual programs.     

非光滑多目标Stackelberg问题的最优性条件

本文研究非光滑多目标Ｓｔａｃｋｅｌｂｅｒｇ问题，给出其有关性质及最优性必要条件，并对若干特例进行了讨论．     

多目标连续小推力深空探测器轨道全局优化

以燃料消耗量最小和飞越小行星最多为性能指标,对多目标连续小推力深空探测器轨道优化,给出了一种组合优化算法。该组合优化算法由全局优化和局部优化组成。全局优化为粗略设计,首先,利用动态规划法全局优化来确定探测系列,即确定从地球出发依次探索的各个小行星以及时间节点;利用静态参数优化算法(即穷举法),在一个大的搜索空间内全面搜索每段飞行轨道的发射窗口,同时,得到每段轨道次优飞行轨道及次优的控制律。然后利用共轭梯度法局部优化来求解每段轨道两点边值问题,获得最优的飞行轨道及最优的控制律。     

动态非光滑Nash协商解必要条件的研究

本文利用非光滑分析理论，采用公理化方法研究了非光滑情形下的动态协商对策问题，给出其Ｎａｓｈ协商解的必要条件，并给予了严格的数学证明．     

广义支持向量机优化问题的极大熵方法

依据最优化理论中的KKT互补条件建立了广义支持向量机的无约束优化模型,并给出了一种有效的光滑化近似解法极大熵方法,为求解支持向量机优化问题提供了一种新途径.该方法特别易于计算机实现,理论分析和数值实验结果表明了模型和算法的可行性和有效性.     

Delay differential equations under nonlinear impulsive control and applications to neural network models

In this paper,a class of delay differential equations with nonlinear impulsive control is discussed.Based on the nonsmooth analysis,criteria of stability are obtained for delay differential equations with nonlinear impulses control under certain conditions.These criteria can be applied to some neural network models.At the end of the paper,two examples are provided to illustrate the feasibility and effectiveness of the proposed results.     

Study of trajectory optimization using terminal-node adaptive-altered spline algorithm

The advantage of using a spline function to evaluate the trajectory parameters optimization is dis-cussed. A new method that using adaptive varied terminal-node spline interpolation for solving trajectory opti-mization is proposed. And it is validated in optimizing the trajectory of guided bombs and extended range guided munitions (ERGM). The solutions are approximate to the real optimization results. The advantage of this arith-metic is that it can be used to solve the trajectory optimization with complex models. Thus, it is helpful for solving the practical engineering optimization problem.     

一类二层多目标决策模型的最优性条件

讨论二层多目标决策模型的最优性条件 ,其中上层集值目标函数由下层偏好最优解的前沿面确定的 .利用集值映射的 Clarke切导数的概念及其性质 ,且假设上层目标函数是可微的 ,给出并证明了该二层多目标决策模型最优解的一阶必要条件 ,所得必要条件由上层目标函数的梯度和下层最优化问题的前沿面的 Clarke切导数构成.     

Distributed Nonsmooth Convex Optimization over Markovian Switching Random Networks with Two Step-Sizes

This paper investigates the distributed convex optimization problem over a multi-agent system with Markovian switching communication networks. The objective function is the sum of each agent's local nonsmooth objective function, which cannot be known by other agents. The communication network is assumed to switch over a set of weight-balanced directed graphs with a Markovian property. The authors propose a consensus sub-gradient algorithm with two time-scale step-sizes to handle the Markovian switching topologies and the absence of global gradient information. With proper selection of step-sizes, the authors prove the almost sure convergence of all agents' local estimates to the same optimal solution when the union graph of the Markovian network' states is strongly connected and the Markovian chain is irreducible. The convergence rate analysis is also given for specific cases.Simulations are given to demonstrate the results.     

MATHEMATICAL PROGRAMMING WITH A CLASS OF NON-SMOOTH FUNCTIONS

1 IntroductionIn 1981, H..,.,,[1] introduced the notion of invexity aJnd showed that for inequality con-strained programs, Karush~Kuhn-Tucker(KKT) conditions are sufficient fOr optimality if thefunctions involved are invex(differentiable) functiolis. Sinc…