求解非线性互补问题的内点正算法

针对非线性互补问题，提出了与其等价的非光滑方程的内点正算法，并在一定条件下证明了该算法的收敛性定理．数值结果表明，该算法是十分有效的．     

非线性规划的拟罚函数—强次可行方向法

本文首先提出非线性规划的拟Ｋｕｈｎ—Ｔｕｃｋｅｒ点和拟罚函数法的概念和思想，然后结合强次可行方向法思想给出问题的两个新型算法，称之为拟罚函数—强次可行方向法．证明了该算法收敛到原问题的拟Ｋｕｈｎ—Ｔｕｃｋｅｒ点．     

带点弧约束的最短路问题：复杂性和算法

本文首先提出了带点弧约束的最短路问题，证明了该问题属于ＮＰ－Ｃ，然后给出了一个伪多项式时间算法．最后给出了最小成本最短路问题的一个时间复杂性为Ｏ（ｎ２）的算法．     

一个求解线性规划的单纯形-内点算法

根据单纯形方法和大步长路径跟踪算法（Ｈｅｒｔｏｇ，Ｒｏｏｓ和Ｔｅｒｌａｋｙ１９９１），对于具有不等式约束的线性规划问题，引进了一个具有组合特性的内点算法．该方法保留了单纯形方法和内点算法的优点，克服了它们的不足，在任何情况下，这个方法都能快速收敛．数值结果也很好地验证了这个结论．     

基于代数等价路径的一致P-函数非线性互补问题的可行内点算法

对一致P-函数非线性互补问题，提出了一种新的基于代数等价路径的可行内点算法，并讨论了计算复杂性．该算法可以在任一内部可行点启动，并且全局收敛；当初始点靠近中心路径时，此算法便成为中心路径跟踪算法，特别对于单调线性互补问题，总迭代次数为O（√nL），其中L是问题的输入长度。     

求解凸二次规划问题的不可行内点算法

该文对一般的凸二次规划问题，给出了一个不可行内点算法，并证明了该算法经过犗（狀２犔）步迭代之后，要么得到问题的一个近似最优解，要么说明该问题在某个较大的区域内无解．     

所有点对之间最快路问题

所有点对之间最快路问题就是要在所有点对(Vs，Vt)之间传送数据δs,t,并找出一条最快的路线．解决所有点对之间最快路问题的关键是产生有效解的等价集合．运用动态点对最短路的算法，本文首先设计了一个时间复杂性为O(mn^2)的产生有效解等价集合的算法，然后研究了静态点对之间最快路问题和动态点对之间最快路问题，其算法的时间复杂性分别为O(mn^2)和O(m^2n^2)．最后本文研究了求和对最小的路问题，证明该问题可以在O(mn^2)时间内解决．     

一类无约束复合非光滑优化的信赖域算法

本文提出了一个易实施的处理一类无约束复合非光滑优化的信赖域算法，并在一定条件下证明了该算法所产生的迭代序列的任何聚点都是原问题的稳定点．     

多目标最优化的一种积分型实现算法

在文[1]中给出了求解多目标最优化的一种积分总极值的概念性算法．本文利用数论中的一致分布佳点集列，较为简便的得出了多目标最优化的积分总极值的实现算法和算法终止准则．并经过有关函数数值计算表明该算法是有效的，可用来求解多目标最优化问题的有效解．     

乘子方法中的参数选择

Di Pillo和Grippo提出的含参数C〉0的增广Lagrangian函数中，使用了最大函数，该函数可能在无穷多个点处不可微．为了克服这个问题，濮定国在2004年提出了一类带新的NCP函数的乘子法．该方法在增广Lagrangian函数和原问题之间存在很好的等价性；同时该方法具有全局收敛性，且在适当假设下，具有超线性收敛率．但是在该方法中，要求参数C充分大．为了实现算法及提高算法效率，本文给出了一个有效选择参数C的方法．     

一类具约束选址模型的组合算法

针对一般具闭凸集约束的单址选址模型,提出具全局收敛性的组合算法．算法在迭代中先采用信赖域技巧,当出现“内循环”时,则改用不做线搜索的梯度法．该算法既具有信赖域算法的优越性,又避免了出现“内循环”时速成的隐迭代．同时,该算法通常不需进行线搜索,较之其它组合算法更加简捷实用．     

Approximation of centroid end-points and switch points for replacing type reduction algorithms

Despite several years of research, type reduction (TR) operation in interval type-2 fuzzy logic system (IT2FLS) cannot perform as fast as a type-1 defuzzifier. In particular, widely used Karnik–Mendel (KM) TR algorithm is computationally much more demanding than alternative TR approaches. In this work, a data driven framework is proposed to quickly, yet accurately, estimate the output of the KM TR algorithm using simple regression models. Comprehensive simulation performed in this study shows that the centroid end-points of KM algorithm can be approximated with a mean absolute percentage error as low as 0.4%. Also, switch point prediction accuracy can be as high as 100%. In conjunction with the fact that simple regression model can be trained with data generated using exhaustive defuzzification method, this work shows the potential of proposed method to provide highly accurate, yet extremely fast, TR approximation method. Speed of the proposed method should theoretically outperform all available TR methods while keeping the uncertainty information intact in the process.     

限制单纯形分解方法中的二次近似

本文给出的算法将信赖域法（TR）与限制单纯形分解方法（RSD）相结合，用于求解RSD方法中的主问题，证明了算法的整体收敛性，给出的算法和RSD方法分别对一些数值例子计算的结果表明算法比RSD方法来得好。     

Combination of trust region method and simplicial decomposition for convex constrained nonlinear optimization

The algorithm presented in this article incorporates the trust region method (TR) into the restricted decomposition algorithm for convex-constrained nonlinear problems (RSDCC) to solve the master problem of RSDCC. The global convergence is proved. The computational comparison between the presented algorithm and RSDCC is given. The results show that the former is much better than the latter.     

A NEW FAMILY OF TRUST REGION ALGORITHMS FOR UNCONSTRAINED OPTIMIZATION

Trust region (TR) algorithms are a class of recently developed algorithms for nonlinear optimization. A new family of TR algorithms for unconstrained optimization, which is the extension of the usual TR method, is presented in this paper. When the objective function is bounded below and continuously, differentiable, and the norm of the Hesse approximations increases at most linearly with the iteration number, we prove the global convergence of the algorithms. Limited numerical results are reported, which indicate that our new TR algorithm is competitive.     

Controllability and stabilization of the programmed motions of a transport robot

A non-linear mathematical model for the motion of a transport robot (TR) with a caterpillar chassis and with drives based on DC motors, which is a non-holonomic electromechanical system, is considered. Non-linear canonical transformations of the coordinates of the state and control space are constructed, which reduce the initial equations of motion of the TR to a simpler canonical form, which is convenient for analysing and synthesizing control systems for the TR. The conditions for the TR to be controllable as a controlled object are found. Algorithms are given for constructing programmed motions (PMs) of the TR. Stabilizing control laws are synthesized under which the PMs of the TR are asymptotically stable and transients of a specified nature are ensured.     

Controllability and stabilization of programmed motions of an automobile-type transport robot

A non-linear model of the motion of an automobile-type transport robot (TR) with absolutely rigid wheels, a steering device and actuators based on DC motors, is considered. Such a model for TR motion is a non-holonomic electromechanical system and, if the dynamics of the actuators and the steering device (forces of elasticity and attenuation in its elements) is ignored, corresponds to the model of automobile motion devised by Lineikin [1]. Non-linear canonical transformations of the state and control space coordinates are constructed which reduce the initial equations of motion of the TR to a simpler canonical form, convenient for the analysis and synthesis of control systems for the TR. These transformations are used to find the conditions for the controllability of the TR as a controlled object. Algorithms are given for constructing programmed controls and programmed motions of the TR. Stabilizing control laws are synthesized that make the programmed motions of the TR asymptotically stable and guarantee that the transients will have preassigned properties     

A restart algorithm for computing fixed points without an extra dimension

An algorithm to compute a fixed point of an upper semicontinuous point to set mapping using a simplicial subdivision is introduced. The new element of the algorithm is that for a given grid it does not start with a subsimplex but with one (arbitrary) point only; the algorithm will terminate always with a subsimplex. This subsimplex yields an approximation of a fixed point and provides the starting point for a finer grid. Some numerical results suggest that this algorithm converges more rapidly than the known algorithms. Moreover, it is very simple to implement the algorithm on the computer.     

The Fixed Point Property for Ordered Sets of Interval Dimension 2

We provide a polynomial time algorithm that identifies if a given finite ordered set is in the class of d2-collapsible ordered sets. For a d2-collapsible ordered set, the algorithm also determines if the ordered set is connectedly collapsible. Because finite ordered sets of interval dimension 2 are d2-collapsible, in particular, the algorithm determines in polynomial time if a given finite ordered set of interval dimension 2 has the fixed point property. This result is also a first step in investigating the complexity status of the question whether a given collapsible ordered set has the fixed point property.     

有向网络中具有一个枢纽点的最小支撑树的计算方法

对有向网络中具有一个枢纽点的支撑树的问题和性质进行了研究,给出了在有向网络图中寻找以某一定点为枢纽点的最小支撑树的计算方法,并对算法的复杂性进行了讨论,最后将该算法应用于实际算例的计算．