仿射变换内点信赖域类方法解单调变分不等式问题

基于Taji引入的一类可微的简单边界约束的严格单调变分不等式问题的势函数,本文提出了仿射变换内点信赖域类修正牛顿法.进一步,作者不仅从理论上证明了该算法的整体收敛性,并且在合理的假设条件下,给出了算法具有局部二次收敛速率.     

线性不等式约束的广义非线性互补问题的仿射内点信赖域方法

提供了一种新的非单调内点回代线搜索技术的仿射内点信赖域方法解线性不等式约束的广义非线性互补问题(GCP).基于广义互补问题构成的半光滑方程组的广义Jacobian矩阵,算法使用l2范数作为半光滑方程组的势函数,形成的信赖域子问题为一个带椭球约束的线性化的二次模型.利用广义牛顿方程计算试探迭代步,通过内点映射回代技术确保迭代点是严格内点,保证了算法的整体收敛性.在合理的条件下,证明了信赖域算法在接近最优点时可转化为广义拟牛顿步,进而具有局部超线性收敛速率.非单调技术将克服高度非线性情况加速收敛进展.最后,数值结果表明了算法的有效性.     

线性不等式约束的广义非线性互补问题的仿射内点信赖域方法

提供了一种新的非单调内点回代线搜索技术的仿射内点信赖域方法解线性不等式约束的广义非线性互补问题(GCP).基于广义互补问题构成的半光滑方程组的广义Jacobian矩阵,算法使用l_2范数作为半光滑方程组的势函数,形成的信赖域子问题为一个带椭球约束的线性化的二次模型.利用广义牛顿方程计算试探迭代步,通过内点映射回代技术确保迭代点是严格内点,保证了算法的整体收敛性.在合理的条件下,证明了信赖域算法在接近最优点时可转化为广义拟牛顿步,进而具有局部超线性收敛速率.非单调技术将克服高度非线性情况加速收敛进展.最后,数值结果表明了算法的有效性.     

An Affine Scaling Interior Point Filter Line-Search Algorithm for Linear Inequality Constrained Minimization

We propose and analyze a new affine scaling interior point method in association with line-search filter technique for solving the linear inequality constrained optimization. We extend an existing filter of Wächter and Biegler [9 A. Wächter and L. Biegler ( 2005 ). Line search filter methods for nonlinear programming: Motivation and global convergence . SIAM J. Comput. 16 : 1 – 31 .[Web of Science ®] , [Google Scholar]] for nonlinear equality constrained problems to linear inequality constraint problems. The two main ingredients of the method are a filter-line-search algorithm which is used to determine step size and an affine-scaling interior point Newton method which is used to generate a search direction. The global convergence of the proposed algorithm is established under some reasonable conditions. Further, the method is shown to be locally Q-superlinearly convergent under the strong second order sufficiency condition. Numerical tests are presented that confirm the robustness and efficiency of the approach.     

一类变分不等式问题的信赖域算法

基于J.M.Peng研究一类变分不等式问题（简记为VIP）时所提出的价值函数，本文提出了求解强单调的VIP的一个新的信赖域算法。和已有的处理VIP的信赖域方法不同的是：它在每步迭代时，不必求解带信赖域界的子问题，仅解一线性方程组而求得试验步。这样，计算的复杂性一般来说可降低。在通常的假设条件下，文中还证明了算法的整体收敛性。最后，在梯度是半光滑和约束是矩形域的假设下，该算法还是超线性收敛的。     

非线性等式约束优化问题的仿射信赖域方法

提出非线性等式和有界约束优化问题的结合非单调技术的仿射信赖域方法. 结合信赖域方法和内点回代线搜索技术, 每一步迭代转到由一般信赖域子问题产生的回代步中且满足严格内点可行条件. 在合理的假设条件下, 证明了算法的整体收敛性和局部超线性收敛速率. 最后, 数值结果表明了所提供的算法具有有效性.     

Global Method for Monotone Variational Inequality Problems with Inequality Constraints

We consider optimization methods for monotone variational inequality problems with nonlinear inequality constraints. First, we study the mixed complementarity problem based on the original problem. Then, a merit function for the mixed complementarity problem is proposed, and some desirable properties of the merit function are obtained. Through the merit function, the original variational inequality problem is reformulated as simple bounded minimization. Under certain assumptions, we show that any stationary point of the optimization problem is a solution of the problem considered. Finally, we propose a descent method for the variational inequality problem and prove its global convergence.     

变分不等式问题的一个新的存在性定理

对于具有一般非空闭凸集约束的变分不等式问题 ,本文给出了一个新的例外族的定义 .通过倩同伦不变定理 ,我们证明了一个择一定理 ,这给出了所考虑问题解的一个充分性条件 .特别 ,我们建立了变分不等式问题的一个新的存在性定理 ,推广了Zhao的一个最近的存在性结果 ,进而也推广了著名Mor啨关于非线性互补问题的存在性定理 .     

Trust region affine scaling algorithms for linearly constrained convex and concave programs

We study a trust region affine scaling algorithm for solving the linearly constrained convex or concave programming problem. Under primal nondegeneracy assumption, we prove that every accumulation point of the sequence generated by the algorithm satisfies the first order necessary condition for optimality of the problem. For a special class of convex or concave functions satisfying a certain invariance condition on their Hessians, it is shown that the sequences of iterates and objective function values generated by the algorithm convergeR-linearly andQ-linearly, respectively. Moreover, under primal nondegeneracy and for this class of objective functions, it is shown that the limit point of the sequence of iterates satisfies the first and second order necessary conditions for optimality of the problem. © 1998 The Mathematical Programming Society, Inc. Published by Elsevier Science B.V.The work of these authors was based on research supported by the National Science Foundation under grant INT-9600343 and the Office of Naval Research under grants N00014-93-1-0234 and N00014-94-1-0340.     

一种内点法解二次规划

二次规划（QP）为NP完全问题，本文研究了一种简单形式的二次规划。 一种基于依赖域子问题和内点法的算法被给出，其全局收敛被给出，特殊情况下，具有局部二次收敛。     

Solving Variational Inequality Problems with Linear Constraints by a Proximal Decomposition Algorithm

The alternating direction method solves large scale variational inequality problems with linear constraints via solving a series of small scale variational inequality problems with simple constraints. The algorithm is attractive if the subproblems can be solved efficiently and exactly. However, the subproblem is itself variational inequality problem, which is structurally also difficult to solve. In this paper, we develop a new decomposition algorithm, which, at each iteration, just solves a system of well-conditioned linear equations and performs a line search. We allow to solve the subproblem approximately and the accuracy criterion is the constructive one developed recently by Solodov and Svaiter. Under mild assumptions on the problem's data, the algorithm is proved to converge globally. Some preliminary computational results are also reported to illustrate the efficiency of the algorithm.     

求解线性不等式约束优化问题的一类信赖域算法

本文对线性不等式约束的非线性规划问题提出了一类信赖域算法,证明了算法所产生的序列的任一聚点为Ｋｕｈｎ－Ｔｕｃｋｅｒ点,并讨论了子问题求解的有效集方法．     

带非线性不等式约束优化问题的信赖域算法

借助于KKT条件和NCP函数,提出了求解带非线性不等式约束优化问题的信赖域算法.该算法在每一步迭代时,不必求解带信赖域界的二次规划子问题,仅需求一线性方程组系统.在适当的假设条件下,它还是整体收敛的和局部超线性收敛的.数值实验结果表明该方法是有效的.     

一类单调变分不等式的非精确交替方向法

交替方向法适合于求解大规模问题.该文对于一类变分不等式提出了一种新的交替方向法.在每步迭代计算中,新方法提出了易于计算的子问题,该子问题由强单调的线性变分不等式和良态的非线性方程系统构成.基于子问题的精确求解,该文证明了算法的收敛性.进一步,又提出了一类非精确交替方向法,每步迭代计算只需非精确求解子问题.在一定的非精确条件下,算法的收敛性得以证明.     

线性约束多目标规划的非单调信赖域算法

本文对线性约束多规划问题提出了一类非单调信赖域算法 ,该方法是可行点法与信赖域技巧的结合 .在一定的条件下证明了算法的全局收敛性 .并进行了数值试验 .     

A Combined Feasible-Infeasible Point Continuation Method for Strongly Monotone Variational Inequality Problems

In this paper, we discuss the variational inequality problems VIP(X, F), where F is a strongly monotone function and the convex feasible set X is described by some inequaliy constraints. We present a continuation method for VIP(X, F), which solves a sequence of perturbed variational inequality problems PVIP(X, F, , ) depending on two parameters 0 and >0. It is worthy to point out that the method will be a feasible point type when =0 and an infeasible point type when >0, i.e., it is a combined feasible–infeasible point (CFIFP for short) method. We analyse the existence, uniqueness and continuity of the solution to PVIP(X, F, , ), and prove that any sequence generated by this method converges to the unique solution of VIP(X, F). Moreover, some numerical results of the algorithm are reported which show the algorithm is effective.     

一种双割线折线法求解信赖域子问题

结合利用Hessian阵的特征值性质,本文提出求解信赖域子问题的一种双割线折线法,它不同于Powell的单折线,Dennis的双折线和赵英良的切线单折线.在适当条件下,分析双割线折线路径的性质,且证明了算法的收敛性.数值试验表明,这种新算法是有效且可行的.     

Variational Inequality and Complementarity Problem for Set－Valued Mapping with Application

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水平线性互补问题的广义中心路径跟踪算法

对水平线性互补问题提出了一种广义中心路径跟踪算法.任意的原始-对偶可行内点均可作为算法的初始点.每步迭代选择“仿射步”与“中心步”的凸组合为新的迭代方向,采用使对偶间隙尽可能减小的最大步长.算法的迭代复杂性为O(√nL).     

使用信赖域策略的投影梯度方法解约束优化问题

本文使用信赖域策略结合投影梯度算法来解约束优化问题,并给出算法及其收敛性。进一步,给出了收敛点具有满足约束问题一阶和二阶必要性的性质。