Linearized ridge-path method for function minimization

A modification based on a linearization of a ridge-path optimization method is presented. The linearized ridge-path method is a nongradient, conjugate direction method which converges quadratically in half the number of search directions required for Powell's method of conjugate directions. The ridge-path method and its modification are compared with some basic algorithms, namely, univariate method, steepest descent method, Powell's conjugate direction method, conjugate gradient method, and variable-metric method. The assessment indicates that the ridge-path method, with modifications, could present a promising technique for optimization.This work was in partial fulfillment of the requirements for the MS degree of the first author at Cairo University, Cairo, Egypt. The authors would like to acknowledge the helpful and constructive suggestions of the reviewer.     

复合材料旋转壳非线性稳定性分析计算

利用前屈曲一致理论和能量变分法分析计算了复合材料旋转壳非线性稳定性.前屈曲应变-位移关系采用非线性的卡门方程,能量积分采用数值积分,用势能最小原理求解前屈曲位移和内力,提出了求解临界载荷的实用计算方法,用FORTRAN语言编制了相应的计算机程序,并给出了算例.     

A COLUMN-SECANT UPDATE TECHNIQUE FOR SOLVING SYSTEM OF NONLINEAR EQUATIONS

In this paper,we present a column-secant modification of the SCC method,which is called the CSSCC method.The CSSCC method uses function values more efficiently than the SCC method,and it is shown that the CSSCC method has better local q-convergence and r-convergence rates than the SCC method.The numerical results show that the CSSCC method is competitive with some well known methods for some standard test problems.     

Efficient numerical methods for pricing American options under stochastic volatility

Five numerical methods for pricing American put options under Heston's stochastic volatility model are described and compared. The option prices are obtained as the solution of a two‐dimensional parabolic partial differential inequality. A finite difference discretization on nonuniform grids leading to linear complementarity problems with M‐matrices is proposed. The projected SOR, a projected multigrid method, an operator splitting method, a penalty method, and a componentwise splitting method are considered. The last one is a direct method while all other methods are iterative. The resulting systems of linear equations in the operator splitting method and in the penalty method are solved using a multigrid method. The projected multigrid method and the componentwise splitting method lead to a sequence of linear complementarity problems with one‐dimensional differential operators that are solved using the Brennan and Schwartz algorithm. The numerical experiments compare the accuracy and speed of the considered methods. The accuracies of all methods appear to be similar. Thus, the additional approximations made in the operator splitting method, in the penalty method, and in the componentwise splitting method do not increase the error essentially. The componentwise splitting method is the fastest one. All multigrid‐based methods have similar rapid grid independent convergence rates. They are about two or three times slower that the componentwise splitting method. On the coarsest grid the speed of the projected SOR is comparable with the multigrid methods while on finer grids it is several times slower. ©John Wiley & Sons, Inc. © 2007 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2007     

KdV方程的特征线混合间断有限元方法

考虑KdV方程的两种特征线性混合间断有限元方法,一种方法建立在标准特征线修正方法的基础上,另一种方法是带有对流项修正的特征线修正方法.利用具有实际物理意义的特征线追踪技巧处理时间导数项和对流项,采用混合间断有限元方法处理三阶导数项,分别证明了两种方法有限元解的唯一性、稳定性和误差估计.     

基于支持向量机的武器系统参数费用模型

在武器系统分析中,建立武器参数费用模型时,首先要挑选特征参数,这里采用R ough理论中的知识约简方法选择武器的特征参数;利用支持向量机建立了参数费用模型;给出了实例和解决此问题的支持向量机源程序.通过实例与线性回归法和神经网络法的结果进行了比较,结果表明支持向量机比较精确和简单.     

Interactive bicriterion solution method and its application to critical path method problems

An interactive solution method is developed for bicriterion mathematical programming (BCMP) problems. The new method, called the dichotomous bicriterion mathematical programming (DBCMP) method, combines Tchebycheff theory and the existing paired comparison method (PCM). The DBCMP method is then compared with the PCM method based on critical path method problems with two conflicting objectives: minimizing the total crashing cost and minimizing the total project completion time. The extension of the DBCMP method to BCMP problems with multiple decision makers is also discussed.     

Simultaneous estimation of thin film thickness and optical properties using two-stage optimization

In this work, we proposed the new method for estimation of the thickness and the optical properties of the thin metal oxide film deposited on a transparent substrate. The developed method uses only transmittance spectra measured. Our method is based on the two stage optimization where the thickness is determined in the outer stage and the optical properties are determined in the inner stage. The differential evolutionary algorithm is used in solving the formulated problem. The proposed method was illustrated in the case study of Titanium dioxide film deposited on a glass substrate. The results indicate that the thickness and the optical properties estimated agree well with the experiment. Moreover, we investigated robustness of the proposed method in the case of transmittance spectra containing noises. The data were modelled by adding random noises ranging between 0 and 30% to the transmittance spectra measured. It is seen that the proposed method has better robustness and performance than the existing method based on pointwise unconstrained minimization approach. In solving the estimation problem, the performance of the proposed method was also compared with the well-known Levenberg?CMarquardt method and single stage differential evolutionary method. The results indicate that the proposed method has better performance than Levenberg?CMarquardt method and single stage differential evolutionary method. Moreover, the proposed method is more robust to random noise than Levenberg?CMarquardt method and single stage differential evolutionary method.     

On preconditioned Uzawa methods and SOR methods for saddle-point problems

This paper studies convergence analysis of a preconditioned inexact Uzawa method for nondifferentiable saddle-point problems. The SOR-Newton method and the SOR-BFGS method are special cases of this method. We relax the Bramble-Pasciak-Vassilev condition on preconditioners for convergence of the inexact Uzawa method for linear saddle-point problems. The relaxed condition is used to determine the relaxation parameters in the SOR-Newton method and the SOR-BFGS method. Furthermore, we study global convergence of the multistep inexact Uzawa method for nondifferentiable saddle-point problems.     

关于割圆连比例解的项氏定理探析

借用项名达易率法、借率法和明安图多项式，本文分析证明关于割圆连比例解的项氏定理，澄清了易主经法的基本原理和方法特征，揭示了易率法与借径术、还原术三者之间的关系。     

On the Convergence of the Cross-Entropy Method

The cross-entropy method is a relatively new method for combinatorial optimization. The idea of this method came from the simulation field and then was successfully applied to different combinatorial optimization problems. The method consists of an iterative stochastic procedure that makes use of the importance sampling technique. In this paper we prove the asymptotical convergence of some modifications of the cross-entropy method.     

解等式约束优化的既约Hessian依赖域方法

本文提出了解等式约束优化的一个信赖域方法,该方法以既约Hessian逐步二次规划为基础,它享有信赖域方法与既约Hessian方法的优点,在通常条件下,证明了算法的全局收敛性。     

An Improved Hybrid Method for Inverse Obstacle Scattering Problems

An improved hybrid method is introduced in this paper as a numerical method to reconstruct the scatterer by far-field pattern for just one incident direction with unknown physical properties of the scatterer. The improved hybrid method inherits the idea of the hybrid method by Kress and Serranho which is a combination of Newton and decomposition method, and it improves the hybrid method by introducing a general boundary condition. The numerical experiments show the feasibility of this method.     

Leap-frogging Newton's method

Using Newton's method as an intermediate step, we introduce an iterative method that approximates numerically the solution of f (x) = 0. The method is essentially a leap-frog Newton's method. The order of convergence of the proposed method at a simple root is cubic and the computational efficiency in general is less, but close to that of Newton's method. Like Newton's method, the new method requires only function and first derivative evaluations. The method can easily be implemented on computer algebra systems where high machine precision is available.     

基于Gini准则的客观组合评价方法研究——以高技术产业技术创新能力评价为例

为了解决多方法评价结论的非一致性问题,提出了一种基于Gini准则的客观组合评价方法。该方法按照每种评价方法的评价值所提供的信息纯度对每种评价方法赋予相应的权重,信息纯度越大,则相应地赋予越大的权重,然后按照赋予的权重进行客观组合评价。并以高技术产业技术创新能力评价为例,验证了Gini准则客观组合评价方法的可操作和相对有效性。基于Gini准则的客观组合评价方法为解决多方法评价结论的非一致性问题提供了新的思路,是组合评价方法研究的有益补充。     

基于蒙特卡洛仿真的理想点决策方法及其应用

首先分析了传统TOPS IS方法的基本原理和计算步骤,指出了传统TOPS IS方法应用时存在的限制与不足,提出了基于计算机蒙特卡洛仿真方法与传统理想点方法相结合的思想,该方法可以利用评测所给的区间值,既方便表述评测结果,也充分利用了评测结果,更加接近实际情况,因而,有助于提高决策质量.最后,通过复杂工程系统设计决策一个算例验证了该法的可行性与有效性.     

A novel interpolating element-free Galerkin (IEFG) method for two-dimensional elastoplasticity

Using the interpolating moving least-squares (IMLS) method to obtain the shape function, we present a novel interpolating element-free Galerkin (IEFG) method to solve two-dimensional elastoplasticity problems. The shape function of the IMLS method satisfies the property of Kronecker δ function, then in the meshless methods based on the IMLS method, the essential boundary conditions can applied directly. Based on the Galerkin weak form, we obtain the formulae of the IEFG method for solving two-dimensional elastoplasticity problems. The IEFG method has some advantages, such as simpler formulae and directly applying the essential boundary conditions, over the conventional element-free Galerkin (EFG) method. The results of three numerical examples show that the computational precision of the IEFG method is higher than that of the EFG method.     

解微分方程组的改进尤拉方法的改进

对改进尤拉方法解微分方程组的方法作了改进,改进的算法与原来算法的计算量一样,但精度比较高.     

一种求多项式方程根的参数并行加速迭代法

推广了一种在无重根情况下,利用Newton类迭代法对同时求多项式零点的加速的迭代法.讨论了该方法的收敛性和收敛阶;最后给出数值算例表明:计算收敛阶和定理结论是一致的,且本算法具有较大的收敛范围.     

正则参数求解的微分进化算法

研究了正则化方法中正则参数的求解问题,提出了利用微分进化算法获取正则参数.微分进化算法属于全局最优化算法,具有鲁棒性强、收敛速度快、计算精度高的优点.把正则参数的求解问题转化为非线性优化问题,通过保持在解空间不同区域中各个点的搜索,以最大的概率找到问题的全局最优解,同时还利用数值模拟将此方法与广义交叉原理、L-曲线准则、逆最优准则等进行了对比,数值模拟结果表明该方法具有一定的可行性和有效性.