FIXED POINTS AND COUPLED FIXED POINTS FOR INCREASING OPERATORS WITH APPLICMIONS TO DIFFERENTIAL INCLUSIONS IN BANACH SPACES

ＦＩＸＥＤＰＯＩＮＴＳＡＮＤＣＯＵＰＬＥＤＦＩＸＥＤＰＯＩＮＴＳＦＯＲＩＮＣＲＥＡＳＩＮＧＯＰＥＲＡＴＯＲＳＷＩＴＨＡＰＰＬＩＣＭＩＯＮＳＴＯＤＩＦＦＥＲＥＮＴＩＡＬＩＮＣＬＵＳＩＯＮＳＩＮＢＡＮＡＣＨＳＰＡＣＥＳＺＨＡＮＧＳＨＩＳＨＥＮＧＡＮＤＨＵ...     

THE REAL CUBE DIFFERENTIAL SYSTEM WITH THREE REAL STRAIGHT LINE SOLUTIONS AND TWO CONJUGATE COMPLEX STRAIGHT LINE SOLUTIONS

ＴＨＥ　ＲＥＡＬ　ＣＵＢＥ　ＤＩＦＦＥＲＥＮＴＩＡＬ　ＳＹＳＴＥＭ　ＷＩＴＨ　ＴＨＲＥＥ　ＲＥＡＬ　ＳＴＲＡＩＧＨＴ　ＬＩＮＥ　ＳＯＬＵＴＩＯＮＳ　ＡＮＤ　ＴＷＯ　ＣＯＮＪＵＧＡＴＥ　ＣＯＭＰＬＥＸ　ＳＴＲＡＩＧＨＴ　ＬＩＮＥ　ＳＯＬＵＴＩＯＮＳＴＨ...     

ON THE EXISTENCE AND UNIQUENESS THEOREMS OF SOLUTIONS FOR A CLASS OF THE SYSTEMS OF MIXED MONOTONE OPERATOR EQUATIONS WITH APPLICATION

ＯＮＴＨＥＥＸＩＳＴＥＮＣＥＡＮＤＵＮＩＱＵＥＮＥＳＳＴＨＥＯＲＥＭＳＯＦＳＯＬＵＴＩＯＮＳＦＯＲＡＣＬＡＳＳＯＦＴＨＥＳＹＳＴＥＭＳＯＦＭＩＸＥＤＭＯＮＯＴＯＮＥＯＰＥＲＡＴＯＲＥＱＵＡＴＩＯＮＳＷＩＴＨＡＰＰＬＩＣＡＴＩＯＮＳＨＥＮＰＥＩＬＯＮＧ...     

ASYMPTOTIC CANONICAL FORMS AND ITERATED LOGARITHM RATE RESULTS OF LEAST SQUARES ESTIMATES FOR UNSTABLE ARMA MODELS

ＡＳＹＭＰＴＯＴＩＣＣＡＮＯＮＩＣＡＬＦＯＲＭＳＡＮＤＩＴＥＲＡＴＥＤＬＯＧＡＲＩＴＨＭＲＡＴＥＲＥＳＵＬＴＳＯＦＬＥＡＳＴＳＱＵＡＲＥＳＥＳＴＩＭＡＴＥＳＦＯＲＵＮＳＴＡＢＬＥＡＲＭＡＭＯＤＥＬＳＺＨＡＮＧＨＵＭＩＮＧ（张虎明）（Ｄｅｐａｒｔｍｅｎ...     

STABILITY IN DIFFERENTIAL EQUATIONS WITH CONTINUOUS AND PIECEWISE CONSTANT ARGUMENTS

ＳＴＡＢＩＬＩＴＹＩＮＤＩＦＦＥＲＥＮＴＩＡＬＥＱＵＡＴＩＯＮＳＷＩＴＨＣＯＮＴＩＮＵＯＵＳＡＮＤＰＩＥＣＥＷＩＳＥＣＯＮＳＴＡＮＴＡＲＧＵＭＥＮＴＳＭｉｎｇ－ＰｏＣｈｅｎＳＴＡＢＩＬＩＴＹＩＮＤＩＦＦＥＲＥＮＴＩＡＬＥＱＵＡＴＩＯＮＳＷＩＴＨＣＯＮ...     

A NOTE FOR THE TOPOLOGICAL CLASSIFICATION OF STRUCTURALLY STABLE QUADRATIC DIFFERENTIAL SYSTEMS WITHOUT LIMIT CYCLES

ＡＮＯＴＥＦＯＲＴＨＥＴＯＰＯＬＯＧＩＣＡＬＣＬＡＳＳＩＦＩＣＡＴＩＯＮＯＦＳＴＲＵＣＴＵＲＡＬＬＹＳＴＡＢＬＥＱＵＡＤＲＡＴＩＣＤＩＦＦＥＲＥＮＴＩＡＬＳＹＳＴＥＭＳＷＩＴＨＯＵＴＬＩＭＩＴＣＹＣＬＥＳ￥ＹｅＷｅｉｙｉｎ（叶惟寅）（ＮａｎｊｉｎｇＮ...     

THE EXISTENCE AND UNIQUENESS AND STABILITY OF ALMOST PERIODIC SOLUTIONS FOR FUNCTIONAL DIFFERENTIAL EQUATIONS WITH INFINITE DELAYS

ＴＨＥＥＸＩＳＴＥＮＣＥＡＮＤＵＮＩＱＵＥＮＥＳＳＡＮＤＳＴＡＢＩＬＩＴＹＯＦＡＬＭＯＳＴＰＥＲＩＯＤＩＣＳＯＬＵＴＩＯＮＳＦＯＲＦＵＮＣＴＩＯＮＡＬＤＩＦＦＥＲＥＮＴＩＡＬＥＱＵＡＴＩＯＮＳＷＩＴＨＩＮＦＩＮＩＴＥＤＥＬＡＹＳＷＡＮＧＱＵＡＮＨＮＹ...     

ON THE EXISTENCE AND UNIQUENESS OF POSITIVE SOLUTIONS FOR A CLASSOF DEGENERATE ELLIPTIC SYSTEMS

ＯＮＴＨＥＥＸＩＳＴＥＮＣＥＡＮＤＵＮＩＱＵＥＮＥＳＳＯＦＰＯＳＩＴＩＶＥＳＯＬＵＴＩＯＮＳＦＯＲＡＣＬＡＳＳＯＦＤＥＧＥＮＥＲＡＴＥＥＬＬＩＰＴＩＣＳＹＳＴＥＭＳ￥ＣＨＥＮＺＨＥＮＴＡＯ（ＤｅｐａｒｔｍｅｎｔｏｆＭａｔｈｅｍａｔｉｃｓ，Ｘｉａｎｇｔ...     

EXACT BOUNDS OF THE MODIFIED LPT ALGORITHMS APPLYING TO PARALLEL MACHINES SCHEDULING WITH NONSIMULTANEOUS MACHINE AVAILABLE TIMES

ＥＸＡＣＴＢＯＵＮＤＳＯＦＴＨＥＭＯＤＩＦＩＥＤＬＰＴＡＬＧＯＲＩＴＨＭＳＡＰＰＬＹＩＮＧＴＯＰＡＲＡＬＬＥＬＭＡＣＨＩＮＥＳＳＣＨＥＤＵＬＩＮＧＷＩＴＨＮＯＮＳＩＭＵＬＴＡＮＥＯＵＳＭＡＣＨＩＮＥＡＶＡＩＬＡＢＬＥＴＩＭＥＳＬＩＮＧＵＯＨＵＩ，Ｈ...     

CRITICAL STOPPING TIMES AND SEMIMARTINGALESOF STOCHASTIC PROCESSES

ＣＲＩＴＩＣＡＬＳＴＯＰＰＩＮＧＴＩＭＥＳＡＮＤＳＥＭＩＭＡＲＴＩＮＧＡＬＥＳＯＦＳＴＯＣＨＡＳＴＩＣＰＲＯＣＥＳＳＥＳＨｕＢｉｊｉｎ（胡必锦）（ＤｅｐａｒｔｍｅｎｔｏｆＭａｔｈｅｍａｔｉｃｓＨＵＳＴＷｕｈａｎ，ＨｕｂｅｉＰ．Ｒ．Ｃ．３．１９９２）Ａ...     

A CLASS OF TRUST REGION METHODS FOR LINEAR INEQUALITY CONSTRAINED OPTIMIZATION AND ITS THEORY ANALYSIS：Ⅰ. ALGORITHM AND GLOBAL CONVERGENCE

A class of trust region methods tor solving linear inequality constrained problems is propo6ed in this paper. It is shown that the algorithm is of global convergence. The algorithm uses a version of the two-slded projection and the strategy of the unconstrained trust region methods. It keeps the good convergence properties of the unconstrained case and has the merits of the projection method. In some sense, our algorithm can be regarded as an extension and improvement of the projected type algorithm.     

无约束非光滑优化问题的信赖域算法及收敛性

1．引言考虑下列无约束非光滑优化问题：其中f为R”上的局部LIPSChitZ函数．本文将11·112简记为11·l．信赖域算法是通过求解一系列子问题3＊B（二，凸）：来求解问题（1）的，其中拉x，·）为j在x点的一阶近似，B为nxn阶对称阵．下面给出信赖域的基本算法TRA：步1·给定...     

一个无约束有限内存信赖域方法及其实现

本文针对大规模无约束优化问题研究了一个新的有限内存信赖域实现方法,提出了一个在有限维（维数≤2m＋1）子空间上精确求解信赖域子问题的方法,大大减少了计算量;分析了方法的收敛性,并详细给出了数值计算方法,最后通过数值实验验证了方法的有效性.     

一个锥模型的自适应信赖域算法及其收敛性

本文研究了无约束最优化问题的基于锥模型的自适应信赖域算法.利用理论分析得到一个新的自适应信赖域半径.算法在每步迭代中以变化的速率、当前迭代点的信息以及水平向量信息调节信赖域半径的大小.从理论上证明了新算法的全局收敛性和Q-二阶收敛性.用数值试验验证了新算法的有效性.推广了已有的自适应信赖域算法的可行性和有效性.     

An improved trust region method for unconstrained optimization

In this paper,we propose an improved trust region method for solving unconstrained optimization problems.Different with traditional trust region methods,our algorithm does not resolve the subproblem within the trust region centered at the current iteration point,but within an improved one centered at some point located in the direction of the negative gradient,while the current iteration point is on the boundary set.We prove the global convergence properties of the new improved trust region algorithm and give the computational results which demonstrate the effectiveness of our algorithm.     

一个新的MBFGS信赖域算法

本文研究了无约束最优化问题.利用MBFGS信赖域算法的基本思想,通过对BFGS校正公式的改进,并结合线搜索技术,提出了一种新的MBFGS信赖域算法,拓宽了信赖域算法的适用范围,并在一定条件下证明了该算法的全局收敛性和超线性收敛性.     

Combining nonmonotone conic trust region and line search techniques for unconstrained optimization

In this paper, we propose a trust region method for unconstrained optimization that can be regarded as a combination of conic model, nonmonotone and line search techniques. Unlike in traditional trust region methods, the subproblem of our algorithm is the conic minimization subproblem; moreover, our algorithm performs a nonmonotone line search to find the next iteration point when a trial step is not accepted, instead of resolving the subproblem. The global and superlinear convergence results for the algorithm are established under reasonable assumptions. Numerical results show that the new method is efficient for unconstrained optimization problems.     

An effective adaptive trust region algorithm for nonsmooth minimization

In this paper, an adaptive trust region algorithm that uses Moreau–Yosida regularization is proposed for solving nonsmooth unconstrained optimization problems. The proposed algorithm combines a modified secant equation with the BFGS update formula and an adaptive trust region radius, and the new trust region radius utilizes not only the function information but also the gradient information. The global convergence and the local superlinear convergence of the proposed algorithm are proven under suitable conditions. Finally, the preliminary results from comparing the proposed algorithm with some existing algorithms using numerical experiments reveal that the proposed algorithm is quite promising for solving nonsmooth unconstrained optimization problems.     

CURVILINEAR PATHS AND TRUST REGION METHODS WITH NONMONOTONIC BACK TRACKING TECHNIQUE FOR UNCONSTRAINED OPTIMIZATION

1. Illtroductioncrust region method is a well-accepted technique in nonlinear optindzation to assure globalconvergence. One of the adVantages of the model is that it does not require the objectivefunction to be convex. Many differellt versions have been suggested in using trust regiontechnique. For each iteration, suppose a current iterate point, a local quadratic model of thefunction and a trust region with center at the point and a certain radius are given. A point thatminimizes the model f…     

约束优化的曲线搜索信赖域算法及其全局收敛性

本文通过对无约束优化ＯＤＥ算法的信赖域分析,提出了约束优化问题的曲线搜索信赖域算法,给出了算法步骤,并讨论了该算法的全局收敛性。