Penalty Parameter for Linearly Constrained 0–1 Quadratic Programming

A linearly constrained 0–1 quadratic programming problem is proved to be equivalent to a continuous concave quadratic problem with an easily computed penalty parameter. Moreover, it is proved that the feasibility of the former problem can be checked by solving the latter.     

Three-Dimensional Nonlinear Analysis of Drill String Structurein Annulus

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An exact penalty function method with global convergence properties for nonlinear programming problems

In this paper a new continuously differentiable exact penalty function is introduced for the solution of nonlinear programming problems with compact feasible set. A distinguishing feature of the penalty function is that it is defined on a suitable bounded open set containing the feasible region and that it goes to infinity on the boundary of this set. This allows the construction of an implementable unconstrained minimization algorithm, whose global convergence towards Kuhn-Tucker points of the constrained problem can be established.     

仿射内点既约投影Hessian算法解非线性约束优化

本文结合非单调内点回代技术,提供了新的仿射信赖域方法解含有非负变量约束和非线性等式约束的优化问题.为求解大规模问题,采用等式约束的Jacobian矩阵的QR分解和两块校正的双边既约Hessian矩阵投影,将问题分解成零空间和值空间两个信赖域子问题.零空间的子问题为通常二次目标函数只带椭球约束的信赖域子问题,而值空间的子问题使用满足信赖域约束参数的值空间投影向量方向.通过引入Fletcher罚函数作为势函数,将由两个子问题结合信赖域策略构成的合成方向,并使用非单调线搜索技术回代于可接受的非负约束内点步长.在合理的条件下,算法具有整体收敛性且两块校正的双边既约Hessian投影法将保持超线性收敛速率.非单调技术将克服高度非线性情况,加快收敛进展.     

A note on the method of multipliers

Implementation of the penalty function method for constrained optimization poses numerical difficulties as the penalty parameter increases. To offset this problem, one often resorts to Newton's method. In this note, working in the context of the penalty function method, we establish an intimate connection between the second-order updating formulas which result from Newton's method on the primal problem and Newton's method on the dual problem.The author wishes to thank Professor R. A. Tapia for his careful review of this note. He has contributed significantly to its content through several crucial observations.     

Crosstalk pattern penalty reduction at 2.5 Gb/s in an SOA employing an assist light around gain transparency wavelength

We evaluate the inter-channel crosstalk in a semiconductor optical amplifier when injecting a high optical power continuous wave, as assist light, inside its active region around the gain transparency wavelength. In this work, the crosstalk of signal₁ (1535 nm) modulated at 2.5 Gb/s, has been induced by signal₂ (1560 nm) modulated at 2.5 Gb/s as well and having an optical input power of −7.5 dBm to simulate a multi-channel transmission. By measuring the bit error rate of signal₁, we show that the pattern penalty induced by the cross-gain modulation can be significantly reduced or even in certain conditions suppressed by the assist light.     

变保费率Cox风险模型的研究

研究了当保费率随理赔强度的变化而变化时C ox风险模型的折现罚金函数,利用后向差分法得到了折现罚金函数所满足的积分方程,进而得到了破产概率,破产前瞬时盈余、破产时赤字的各阶矩所满足的积分方程.最后给出当理赔额服从指数分布,理赔强度为两状态的马氏过程时破产概率的拉普拉斯变换,对一些具体数值计算出了破产概率的表达式.     

An Eulerian‐Lagrangian discontinuous Galerkin method for transient advection‐diffusion equations

We develop an Eulerian‐Lagrangian discontinuous Galerkin method for time‐dependent advection‐diffusion equations. The derived scheme has combined advantages of Eulerian‐Lagrangian methods and discontinuous Galerkin methods. The scheme does not contain any undetermined problem‐dependent parameter. An optimal‐order error estimate and superconvergence estimate is derived. Numerical experiments are presented, which verify the theoretical estimates.© 2007 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 2007     

A primal-dual Newton-type algorithm for geometric programs with equality constraints

An augmented Lagrangian algorithm is used to find local solutions of geometric programming problems with equality constraints (GPE). The algorithm is Newton's method for unconstrained minimization. The complexity of the algorithm is defined by the number of multiplications and divisions. By analyzing the algorithm we obtain results about the influence of each parameter in the GPE problem on the complexity of an iteration. An attempt is made to estimate the number of iterations needed for convergence. In practice, certain hypotheses are tested, such as the influence of the penalty coefficient update formula, the distance of the starting point from the optimum, and the stopping criterion. For these tests, a random problem generator was constructed, many problems were run, and the results were analyzed by statistical methods.The authors are grateful to Dr. J. Moré, Argonne National Laboratory for his valuable comments.This research was partially funded by the Fund for the Advancement of Research at the Technion and by the Applied Mathematical Sciences Research Program (KC-04-02), Office of Energy Research, US Department of Energy, Contract No. W-31-109-Eng-38.     

Approximate Augmented Lagrangian Functions and Nonlinear Semidefinite Programs

In this paper, an approximate augmented Lagrangian function for nonlinear semidefinite programs is introduced. Some basic properties of the approximate augmented Lagrange function such as monotonicity and convexity are discussed. Necessary and sufficient conditions for approximate strong duality results are derived. Conditions for an approximate exact penalty representation in the framework of augmented Lagrangian are given. Under certain conditions, it is shown that any limit point of a sequence of stationary points of approximate augmented Lagrangian problems is a KKT point of the original semidefinite program and that a sequence of optimal solutions to augmented Lagrangian problems converges to a solution of the original semidefinite program.