Feasibility and Structural Feature on Monotone Second-Order Cone Linear Complementarity Problems in Hilbert Space

Given a real finite-dimensional or infinite-dimensional Hilbert space H with a Jordan product, the second-order cone linear complementarity problem(SOCLCP)is considered. Some conditions are investigated, for which the SOCLCP is feasible and solvable for any element q?H. The solution set of a monotone SOCLCP is also characterized. It is shown that the second-order cone and Jordan product are interconnected.

A New Conjugate Gradient Projection Method for Solving Stochastic Generalized Linear Complementarity Problems

In this paper, a class of the stochastic generalized linear complementarity problems with finitely many elements is proposed for the first time. Based on the Fischer-Burmeister function, a new conjugate gradient projection method is given for solving the stochastic generalized linear complementarity problems. The global convergence of the conjugate gradient projection method is proved and the related numerical results are also reported.

Modulus-Based Matrix Splitting Iteration Methods for a Class of Stochastic Linear Complementarity Problem

For the expected value formulation of stochastic linear complementarity problem, we establish modulus-based matrix splitting iteration methods. The convergence of the new methods is discussed when the coefficient matrix is a positive definite matrix or a positive semi-definite matrix, respectively. The advantages of the new methods are that they can solve the large scale stochastic linear complementarity problem, and spend less computational time. Numerical results show that the new methods are efficient and suitable for solving the large scale problems.

A New Complementarity Function and Applications in Stochastic Second-Order Cone Complementarity Problems

This paper considers the so-called expected residual minimization(ERM)formulation for stochastic second-order cone complementarity problems,which is based on a new complementarity function called termwise residual complementarity function associated with second-order cone.We show that the ERM model has bounded level sets under the stochastic weak R0-property.We further derive some error bound results under either the strong monotonicity or some kind of constraint qualifications.Then,we apply the Monte Carlo approximation techniques to solve the ERM model and establish a comprehensive convergence analysis.Furthermore,we report some numerical results on a stochastic second-order cone model for optimal power flow in radial networks.

A Class of Second-Order Cone Eigenvalue Complementarity Problems for Higher-Order Tensors

In this paper,we consider the second-order cone tensor eigenvalue complementarity problem(SOCTEiCP)and present three different reformulations to the model under consideration.Specifically,for the general SOCTEiCP,we first show its equivalence to a particular variational inequality under reasonable conditions.A notable benefit is that such a reformulation possibly provides an efficient way for the study of properties of the problem.Then,for the symmetric and sub-symmetric SOCTEiCPs,we reformulate them as appropriate nonlinear programming problems,which are extremely beneficial for designing reliable solvers to find solutions of the considered problem.Finally,we report some preliminary numerical results to verify our theoretical results.

RobustL_1 model reduction for stochastic time-delay systems

This paper investigates the problem of robust L1 model reduction for continuous-time uncertain stochastic time-delay systems. For a given mean-square stable system, our purpose is to construct reduced-order systems, such that the error system between these two models is mean-square asymptotically stable and has a guaranteed L1 (also called peak-to-peak) performance. The peak-to-peak gain criterion is first established for stochastic time-delay systems, and the corresponding model reduction problem is solved by using projection lemma. Sufficient conditions are obtained for the existence of admissible reduced-order models in terms of linear matrix inequalities (LMIs) plus matrix inverse constraints. Since these obtained conditions are not expressed as strict LMIs, the cone complementarity linearization (CCL) method is exploited to cast them into nonlinear minimization problems subject to LMI constraints, which can be readily solved by standard numerical software. In addition, the development of reduced-order models with special structures, such as the delay-free model, is also presented. The efficiency of the proposed methods is demonstrated via a numerical example.

GUS-property for Lorentz cone linear complementarity problems on Hilbert spaces

Given a real(finite-dimensional or infinite-dimensional) Hilbert space H with a Jordan product,we consider the Lorentz cone linear complementarity problem,denoted by LCP(T,Ω,q),where T is a continuous linear operator on H,ΩH is a Lorentz cone,and q ∈ H.We investigate some conditions for which the problem concerned has a unique solution for all q ∈ H(i.e.,T has the GUS-property).Several sufficient conditions and several necessary conditions are given.In particular,we provide two suficient and necessary conditions of T having the GUS-property.Our approach is based on properties of the Jordan product and the technique from functional analysis,which is different from the pioneer works given by Gowda and Sznajder(2007) in the case of finite-dimensional spaces.

解三维摩擦接触问题的一个二阶锥线性互补法

针对三维摩擦接触问题的求解,给出了一种基于参变量变分原理的二阶锥线性互补法。首先,基于三维Coulomb摩擦锥在数学表述上属于二阶锥的事实,利用二阶锥规划对偶理论,建立了三维Coulomb摩擦接触条件的参变量二阶锥线性互补模型,它是二维Coulomb摩擦接触条件参变量线性互补模型在三维情形下的自然推广;随后,利用参变量变分原理与有限元方法,建立了求解三维摩擦接触问题的二阶锥线性互补法。较之于将三维Coulomb摩擦锥进行显式线性化的线性互补法,该方法无需对三维Coulomb摩擦锥进行线性化,因而在保证精度的前提下所解问题的规模要小很多。最后通过算例展示了该方法的特点。

具有补偿的两阶段随机二阶锥规划问题的一个等价形式

确定的二阶锥规划(DSOCP)是一类凸优化问题,为处理DSOCP的数据的不确定性,具有补偿的随机二阶锥规划问题备受关注.有许多重要的实际问题,如随机欧几里得设施位置问题、具有损失风险约束的投资组合优化问题、最优覆盖随机椭球问题等均可建模为具有补偿的随机二阶锥规划问题,有效求解方法多为内点法.讨论具有补偿的随机两阶段二阶锥规划问题,在Slater约束规范条件下,探讨了第二阶段问题的对偶问题及最优值函数的次微分性质,在随机变量的概率分布具有有限支撑的条件下,给出了两阶段随机二阶锥规划问题的一个等价的线性二阶锥规划问题.

线性二阶锥权互补问题的非精确非单调光滑化牛顿法

针对线性二阶锥权互补问题,提出一种新的非精确非单调光滑化牛顿法.首先,基于新的含参数光滑函数,将线性二阶锥权互补问题转化为一个光滑方程组;然后,给出求解该方程组的新非精确非单调光滑化牛顿法;最后,在半正定矩阵假设下,证明该算法全局收敛和局部超线性收敛.数值结果表明,该算法稳定、有效.

求解随机二阶锥线性互补问题的期望残差最小化方法

引入期望残差最小化(ERM)方法来求解随机二阶锥线性互补问题.在非负象限内,利用ERM方法求解随机线性互补问题是可行的,为此将非负象限内的随机线性互补问题延伸到二阶锥内.首先,介绍了二阶锥矢量相关的若尔当积及谱分解等预备知识.然后,通过二阶锥互补函数FB函数将随机二阶锥线性互补问题转化为极小化问题.以预备知识为基础证明了若尔当积下的x2与x 2的关系,并进一步证明了离散型目标函数解的存在性与收敛性.最后,证明利用ERM方法解随机二阶锥互补问题是可行的.

一类积分函数的SC^1性质

研究一类积分函数的半光滑性和SC1性质,所得结果在求解随机线性互补问题的Newton算法的收敛性分析中起关键作用.

线性二阶锥权互补问题的非单调无导数下降算法

提出非单调无导数下降算法,用于求解线性二阶锥权互补问题。构造一个效益函数,分析其水平集有界性。提出的算法在计算步长时进行非单调线搜索,搜索方向在一定假设下满足下降条件。理论证明算法全局收敛,数值结果验证算法有效。

解一类随机线性互补的可行光滑牛顿法(英文)

目的研究一类随机线性互补问题。方法提出了可行的光滑牛顿法求解该随机线性互补问题。用了一个近似函数,当光滑参数是正的时候,该函数是光滑的。当一定的条件满足时,用一个新的点更新光滑参数。结果在一定的条件下,收敛性得到了保证。结论数值实验说明本文的方法是有效的。

求解随机广义垂直线性互补问题的一类样本均值近似无约束极小化方法

提出了一类样本均值无约束极小化方法求解一类随机广义垂直线性互补问题.提出一类新型的广义垂直互补问题的光滑化函数,并基于此函数构造了一系列无约束优化问题.基于矩阵的性质建立了方法的收敛性.通过数值实验验证了算法的有效性.

求解随机线性互补问题的社会认知算法

针对传统算法求解随机线性互补问题时需要给定初始点、计算梯度,并且解不唯一时无法获得多个最优解的困难,提出了求解随机线性互补问题的社会认知算法.将随机线性互补问题转化为含有随机变量的约束优化问题,并通过平均抽样逼近该随机约束优化问题,利用社会认知算法求解该优化问题.数值试验结果表明社会认知算法是求解随机线性互补问题的有效算法.

混合随机线性二阶锥互补问题的求解方法

由于随机问题一般不存在适合所有情况的解,借助于期望残差极小化模型,给出了一种混合随机线性二阶锥互补问题的求解方法.利用蒙特卡罗方法来近似期望残差极小化问题,讨论了期望残差极小化问题及其近似问题的强制性,给出了近似问题收敛性的证明,最后把所得到的理论结果应用到了一个具有辐射状网络结构的电力系统随机最优潮流问题,并给出了数值实验.

线性二阶锥互补问题的非单调线搜索光滑算法

在光滑算法的基础上提出线性二阶锥互补问题的基于非单调线搜索的光滑算法。该算法引入了一个非单调因子,利用这个非单调因子来控制线搜索的非单调程度,同时给出算法的全局收敛性及局部超线性收敛性分析,最后给出算法的数值实验,比较不同的非单调因子对同一问题计算结果的影响,结果表明非单调因子对计算结果影响很大。

二阶锥线性互补问题的低阶罚函数算法

本文研究了二阶锥线性互补问题的低阶罚函数算法.利用低阶罚函数算法将二阶锥线性互补问题转化为低阶罚函数方程组,获得了低阶罚函数方程组的解序列在特定条件下以指数速度收敛于二阶锥线性互补问题解的结果,推广了二阶锥线性互补问题的幂罚函数算法.数值实验结果验证了算法的有效性.

线性圆锥互补问题的光滑化牛顿法

给出求解线性圆锥互补问题一种新的光滑化牛顿法.首先,基于一个圆锥互补函数的光滑化函数,将线性圆锥互补问题转化成一个方程组,然后用光滑化牛顿法求解该方程组;其次,在适当假设下,证明该算法具有全局收敛性和局部二阶收敛性.数值结果表明,该算法求解线性圆锥互补问题所需的CPU时间和迭代次数均较少,且相对稳定,从而证明了算法的有效性.