一种基于LVI求解二次规划问题的数值算法

给出并研究了一种数值算法(简称94LVI算法),用于求解带等式和双端约束的二次规划问题. 这类带约束的二次规划问题首先被转换为线性变分不等式问题,该问题等价于分段线性投影等式.接着使用94LVI算法求解上述分段线性投影等式,从而得到QP问题的最优解. 进一步给出了94LVI算法的全局收敛性证明. 94LVI算法与经典有效集算法的对比实验结果证实了给出的94LVI算法在求解二次规划问题上的高效性与优越性.     

具有线性等式和不等式约束的非线性规划的一个算法

§1.引言既约梯度法是求解非线性规划的一类方法.我们目前只看到约束为线性等式或非线性等式的既约梯度法,对于线性不等式或非线性不等式约束的情形还没有相应的既约梯度法.如果通过松驰变量把线性不等式约束化成线性等式的情形处理,则要增加变量的维数,而这是与既约梯度法的思想背道而驰的.在本文中,我们结合既约梯度法与 Ritter在文献[3]中的思想,对具有线性等式和不等式约束的非线性规划问题给出了一种算法,它保留了既约梯度法降低维数的优点,又简化了 Ritter 在[3]中给出的算法.另外,我们还证明了算法的收敛性.     

带等式约束二次规划子问题的滤子SQP算法

一类求解非线性规划问题的滤子序列二次规划(SQP)方法被提出.为了提高收敛速度,给目标函数和约束违反度函数都设置了斜边界.二次规划子问题(QP)设置为两项:不等式约束QP和等式约束QP.两个子问题产生的搜索方向进行线性迭加后为算法的搜索方向.这样的设置可以改善收敛性,并调节算法运行中的一些不良效果.在较温和的条件下,可得到全局收敛性.     

线性约束三次规划问题的全局最优性必要条件和最优化算法

讨论了带线性不等式约束三次规划问题的最优性条件和最优化算法. 首先, 讨论了带有线性不等式约束三次规划问题的 全局最优性必要条件. 然后, 利用全局最优性必要条件, 设计了解线性约束三次规划问题的一个新的局部最优化算法(强局部最优化算法). 再利用辅助函数和所给出的新的局部最优化算法, 设计了带有线性不等式约束三 规划问题的全局最优化算法. 最后, 数值算例说明给出的最优化算法是可行的、有效的.     

线性等式约束多目标规划的一个降维算法

本文提出具有线性等式约束多目标规划问题的一个降维算法．当目标函数全是二次或线性但至少有一个二次型时，用线性加权法转化原问题为单目标二次规划，再用降维方法转化为求解一个线性方程组．若目标函数非上述情形，首先用线性加权法将原问题转化为具有线性等式约束的非线性规划，然后，对这一非线性规划的目标函数二次逼近，构成线性等式约束二次规划序列，用降维法求解，直到满足精度要求为止．     

等式约束不定最小二乘问题的双曲MGS消去算法

众所周知,加权法是解等式约束不定最小二乘问题的方法之一.通过探讨极限意义下,双曲MGS算法解对应加权问题的本质,得到一类消去算法.实验表明,该算法以和文献中现有的GHQR算法达到一样的精度,但实际计算量只需要GHQR算法的一半.     

初始点任意的一个非线性优化的广义梯度投影法

广义投影算法的优点是避免转轴运算。它成功地给出了线性约束问题、初始点任意的只带非线性不等式约束问题，以及利用辅助规划来处理带等式与不等式约束问题的算法．后者完满地解决了投影算法对于非线性等式约束问题的处理，但要求满足不等式约束的初始点．本文据此利用广义投影与罚函数技巧给出了一个初始点任意的等式与不等式约束问题的算法，省去了求初始解的计算，并保持了上述方法的优点，证明了算法的全局收敛性     

某类等式约束二次规划问题的一个共轭方向法

本文提出了一种求解某类等式约束二次规划问题的一个共轭方向迭代法，并给出了算法的有限终止性证明．同时我们把此算法推广到不等式约束二次规划问题中，从而得到了一种求解不等式约束二次规划问题的算法．     

非线性最优化一个可行序列等式约束二次规划算法

本文针对非线性不等式约束优化问题,提出了一个新的可行序列等式约束二次规划算法．在每次迭代中,该算法只需求解三个相同规模且仅含等式约束的二次规划(必要时求解一个辅助的线性规划),因而其计算工作量较小．在一般的条件下,证明了算法具有全局收敛及超线性收敛性．数值实验表明算法是有效的．     

一类线性约束矩阵不等式及其最小二乘问题

本文主要考虑一类线性矩阵不等式及其最小二乘问题,它等价于相应的矩阵不等式最小非负偏差问题.之前相关文献提出了求解该类最小非负偏差问题的迭代方法,但该方法在每步迭代过程中需要精确求解一个约束最小二乘子问题,因此对规模较大的问题,整个迭代过程需要耗费巨大的计算量.为了提高计算效率,本文在现有算法的基础上,提出了一类修正迭代方法.该方法在每步迭代过程中利用有限步的矩阵型LSQR方法求解一个低维矩阵Krylov子空间上的约束最小二乘子问题,降低了整个迭代所需的计算量.进一步运用投影定理以及相关的矩阵分析方法证明了该修正算法的收敛性,最后通过数值例子验证了本文的理论结果以及算法的有效性.     

Using Tabu search in CSPS

A heuristic method TABU-CSP using Tabu Search (TS) is described for solving Constraint Satisfaction Problems (CSPs). The method is started with a complete but inconsistent solution of a binary CSP and obtained in prespecified number of iterations either a consistent solution or a near optimal solution with an acceptable number of conflicts. The repair in the solution at each iterative step is done by using two heuristics alternatively. The first heuristic is a min-conflict heuristic that chooses a variable with the maximum number of conflicts and reassigns it the value which leads to the minimum number of conflicts. If the acceptable solution is not reached after the search continued for a certain number of iterations, the min-conflict heuristic is changed and the variable selected least number of times is chosen for repair. If an acceptable solution is not reached, the method switches back to the min-conflict heuristic and proceeds further. This allowed the method to explore a different region of search space for the solution as well as to prevent cycling. The demonstration of the method is shown on a toy problem [9] which has no solution. The method is then tested on various randomly generated CSPs with different starting solutions. The performance of the proposed method in terms of the average number of consistency is checked and the average number of conflicts is compared with that of the Branch and Bound (BB) method used to obtain the same solution. In almost all cases, the proposed method moves faster to the acceptable solution than BB.     

一类海-气振子ENSO模型的同伦分析解法

研究了一个ENSO海-气时滞振子模型.利用同伦分析方法,得到了该模型解的近似展开式,通过与特殊情况下的精确解比较,得到的二级近似解具有较高的精度.     

On the numerical solution of Cauchy type singular integral equations by the collocation method

The collocation method for the numerical solution of Fredholm integral equations of the second kind is applied, properly modified, to the numerical solution of Cauchy type singular integral equations of the first or the second kind but with constant coefficients. This direct method of numerical solution of Cauchy type singular integral equations is compared afterwards with the corresponding method resulting from applying the collocation method to the Fredholm integral equation of the second kind equivalent to the Cauchy type singular integral equation, as well as with another method, based also on the regularization procedure, for the numerical solution of the same class of equations. Finally, the convergence of the method is discussed.     

Meshless formulation to two-dimensional nonlinear problem of generalized Benjamin–Bona–Mahony–Burgers through singular boundary method: Analysis of stability and convergence

In this study, the singular boundary method (SBM) is employed for the simulation of nonlinear generalized Benjamin–Bona–Mahony–Burgers problem with initial and Dirichlet-type boundary conditions. The θ-weighted finite difference method is used to discretize the time derivatives. Then the original equations are split into a system of partial differential equations. A splitting scheme is applied to split the solution of the inhomogeneous governing equation into homogeneous solution and particular solution. To solve this system, the method of particular solution (MPS) in combination with the SBM is used where the SBM is used for homogeneous solution and MPS is used for particular solution. Furthermore, the stability and convergence of the proposed method is conducted. Finally, several numerical examples with different domains are provided and compared with the exact analytical solutions to show the accuracy and efficiency in comparison with existing other methods.     

Automatic solution of optimal-control problems. I. simplest problem in the calculus of variations

An automatic method for obtaining the numerical solution for the simplest problem in the calculus of variations is described. The nonlinear two-point boundary-value Euler-Lagrange equation is solved using the Newton-Raphson method for obtaining successive approximations of the solution. The derivatives required for the solution of the problem are computed automatically using the table method. The user of the program need only input the integrand of the objective function in the calculus-of-variations problem and specify the boundary conditions. None of the derivatives usually associated with the Euler-Lagrange equation and the Newton-Raphson method need be calculated by hand. An example is given with numerical results. The automatic solution of the simplest problem in the calculus of variations in this paper is considered to be the first step in the automatic solution of more general optimal-control problems.     

时滞Lokta-Volterra生态模型的同伦分析解法

研究了时滞Lolta-Volterra生态模型.利用同伦分析方法,得到了该模型解的近似展开式,并对近似解与数值解进行了比较.比较结果表明,近似解具有较高的精度,该方法用于生态模型研究可行.     

Embedding evolutionary strategy in ordinal optimization for hard optimization problems

This work proposes a method for embedding evolutionary strategy (ES) in ordinal optimization (OO), abbreviated as ESOO, for solving real-time hard optimization problems with time-consuming evaluation of the objective function and a huge discrete solution space. Firstly, an approximate model that is based on a radial basis function (RBF) network is utilized to evaluate approximately the objective value of a solution. Secondly, ES associated with the approximate model is applied to generate a representative subset from a huge discrete solution space. Finally, the optimal computing budget allocation (OCBA) technique is adopted to select the best solution in the representative subset as the obtained “good enough” solution. The proposed method is applied to a hotel booking limits (HBL) problem, which is formulated as a stochastic combinatorial optimization problem with a huge discrete solution space. The good enough booking limits, obtained by the proposed method, have promising solution quality, and the computational efficiency of the method makes it suitable for real-time applications. To demonstrate the computational efficiency of the proposed method and the quality of the obtained solution, it is compared with two competing methods – the canonical ES and the genetic algorithm (GA). Test results demonstrate that the proposed approach greatly outperforms the canonical ES and GA.     

A meshless method based on boundary integral equations and radial basis functions for biharmonic-type problems

This paper presents a meshless method, which replaces the inhomogeneous biharmonic equation by two Poisson equations in terms of an intermediate function. The solution of the Poisson equation with the intermediate function as the right-hand term may be written as a sum of a particular solution and a homogeneous solution of a Laplace equation. The intermediate function is approximated by a series of radial basis functions. Then the particular solution is obtained via employing Kansa’s method, while the homogeneous solution is approximated by using the boundary radial point interpolation method by means of boundary integral equations. Besides, the proposed meshless method, in conjunction with the analog equation method, is further developed for solving generalized biharmonic-type problems. Some numerical tests illustrate the efficiency of the method proposed.     

双变量LMEs一种异类约束最小二乘解的MCG算法

借鉴求线性矩阵方程组(LMEs)同类约束最小二乘解的修正共轭梯度法,建立了求双变量LMEs的一种异类约束最小二乘解的修正共轭梯度法,并证明了该算法的收敛性.在不考虑舍入误差的情况下,利用该算法不仅可在有限步计算后得到LMEs的一组异类约束最小二乘解,而且选取特殊初始矩阵时,可求得LMEs的极小范数异类约束最小二乘解.另外,还可求得指定矩阵在该LMEs的异类约束最小二乘解集合中的最佳逼近.算例表明,该算法是有效的.     

奇异杂交边界点方法求解泊松方程

As a boundary-type meshless method,the singular hybrid boundary node method(SHBNM)is based on the modified variational principle and the moving least square(MLS)approximation,so it has the advantages of both boundary element method(BEM)and meshless method.In this paper,the dual reciprocity method(DRM)is combined with SHBNM to solve Poisson equation in which the solution is divided into particular solution and general solution.The general solution is achieved by means of SHBNM,and the particular solution is approximated by using the radial basis function(RBF).Only randomly distributed nodes on the bounding surface of the domain are required and it doesn't need extra equations to compute internal parameters in the domain.The postprocess is very simple.Numerical examples for the solution of Poisson equation show that high convergence rates and high accuracy with a small node number are achievable.