Modified Augmented Lagrange Multiplier Methods for Large-Scale Chemical Process Optimization

Chemical process optimization can be described as large-scale nonlinear constrained minimization. The modified augmented Lagrange multiplier methods (MALMM) for large-scale nonlinear constrained minimization are studied in this paper. The Lagrange function contains the penalty terms on equality and inequality constraints and the methods can be applied to solve a series of bound constrained sub-problems instead of a series of unconstrained sub-problems. The steps of the methods are examined in full detail. Numerical experiments are made for a variety of problems, from small to very large-scale, which show the stability and effectiveness of the methods in large-scale problems.

A Parameter-Free Approach to Determine the Lagrange Multiplier in the Level Set Method by Using the BESO

A parameter-free approach is proposed to determine the Lagrange multiplier for the constraint of material volume in the level set method.It is inspired by the procedure of determining the threshold of sensitivity number in the BESO method.It first computes the difference between the volume of current design and the upper bound of volume.Then,the Lagrange multiplier is regarded as the threshold of sensitivity number to remove the redundant material.Numerical examples proved that this approach is effective to constrain the volume.More importantly,there is no parameter in the proposed approach,which makes it convenient to use.In addition,the convergence is stable,and there is no big oscillation.

冗余机械臂轨迹的增广Lagrange-改进粒子群算法优化

为了减小冗余机械臂的工作时间和运动冲击,提出了基于增广lagrange-多学习行为粒子群算法的轨迹优化方法。介绍了7自由度冗余机械臂的构型,以减小工作时间和运动冲击为目标建立了约束优化模型。使用增广拉格朗日乘子法将约束优化问题转化为无约束优化问题。在粒子群算法中引入了3种新型的粒子学习行为,并依据学习行为价值确定粒子选择各学习行为的概率,既保证了粒子多样性也保证了收敛的快速性。经实验验证,多学习行为粒子群算法优化的轨迹在时间和冲击方面好于传统粒子群算法优化轨迹,且改进粒子群算法优化轨迹平滑,运动参数在约束范围内,以上结果验证了增广lagrange-多学习行为粒子群算法在机械臂轨迹优化方面的有效性和优越性。

Fully Coupled Fluid-Structure Interaction Model Based on Distributed Lagrange Multiplier/Fictitious Domain Method

This paper, with a finite element method, studies the interaction of a coupled incompressible fluid-rigid structure system with a free surface subjected to external wave excitations. With this fully coupled model, the rigid structure is taken as ＂fictitious＂ fluid with zero strain rate. Both fluid and structure are described by velocity and pressure. The whole domain, including fluid region and structure region, is modeled by the incompressible Navier-Stokes equations which are discretized with fixed Eulerian mesh. However, to keep the structure＇ s rigid body shape and behavior, a rigid body constraint is enforced on the ＂fictitious＂ fluid domain by use of the Distributed Lagrange Multipher/Fictitious Domain （DLM/ FD） method which is originally introduced to solve particulate flow problems by Glowinski et al. For the verification of the model presented herein, a 2D numerical wave tank is established to simulate small amplitude wave propagations, and then numerical results are compared with analytical solutions. Finally, a 2D example of fluid-structure interaction under wave dynamic forces provides convincing evidences for the method excellent solution quality and fidelity.

A Modified Lagrange Method for Solving Convex Quadratic Optimization Problems

In this paper, a modified version of the Classical Lagrange Multiplier method is developed for convex quadratic optimization problems. The method, which is evolved from the first order derivative test for optimality of the Lagrangian function with respect to the primary variables of the problem, decomposes the solution process into two independent ones, in which the primary variables are solved for independently, and then the secondary variables, which are the Lagrange multipliers, are solved for, afterward. This is an innovation that leads to solving independently two simpler systems of equations involving the primary variables only, on one hand, and the secondary ones on the other. Solutions obtained for small sized problems (as preliminary test of the method) demonstrate that the new method is generally effective in producing the required solutions.

Modified Lagrange Multiplier Method and Generalized Variational Principle in Fluid Mechanics

The Lagrange multiplier method plays an important role in establishing generalized variational principles notonly in tluid mechallics. but also in elasticity. Sometimes, however, one may come across variational crisis(somemultipliers vanish identically). failing to achieve his aim. The crisis is caused by the fact that the Inultipliers are treatedas independent variables in the process of variatioll. but after identification they become functions of the originalindependent variables. To overcome it, a Inodified Lagrange multiplier method or semi-inverse method has beenproposed to deduce generalized varistional principles. Some e-camples are given to illustrate its convenience andeffectiveness of the novel method.

Distributed Lagrange Multiplier/Fictitious Domain Finite Element Method for a Transient Stokes Interface Problem with Jump Coefficients

The distributed Lagrange multiplier/fictitious domain(DLM/FD)-mixed finite element method is developed and analyzed in this paper for a transient Stokes interface problem with jump coefficients.The semi-and fully discrete DLM/FD-mixed finite element scheme are developed for the first time for this problem with a moving interface,where the arbitrary Lagrangian-Eulerian(ALE)technique is employed to deal with the moving and immersed subdomain.Stability and optimal convergence properties are obtained for both schemes.Numerical experiments are carried out for different scenarios of jump coefficients,and all theoretical results are validated.

Accelerated Matrix Recovery via Random Projection Based on Inexact Augmented Lagrange Multiplier Method

In this paper, a unified matrix recovery model was proposed for diverse corrupted matrices. Resulting from the separable structure of the proposed model, the convex optimization problem can be solved efficiently by adopting an inexact augmented Lagrange multiplier (IALM) method. Additionally, a random projection accelerated technique (IALM+RP) was adopted to improve the success rate. From the preliminary numerical comparisons, it was indicated that for the standard robust principal component analysis (PCA) problem, IALM+RP was at least two to six times faster than IALM with an insignificant reduction in accuracy; and for the outlier pursuit (OP) problem, IALM+RP was at least 6.9 times faster, even up to 8.3 times faster when the size of matrix was 2 000×2 000.

Optimizing Forest Sampling by Using Lagrange Multipliers

In two-phase sampling, or double sampling, from a population with size N we take one, relatively large, sample size n. From this relatively large sample we take a small sub-sample size m, which usually costs more per sample unit than the first one. In double sampling with regression estimators, the sample of the first phase n is used for the estimation of the average of an auxiliary variable X, which should be strongly related to the main variable Y (which is estimated from the sub-sample m). Sampling optimization can be achieved by minimizing cost C with fixed var Y, or by finding a minimum var Y for fixed C. In this paper we optimize sampling with use of Lagrange multipliers, either by minimizing variance of Y and having predetermined cost, or by minimizing cost and having predetermined variance of Y.

The Mortar Element Method with Lagrange Multipliers for Stokes Problem

In this paper,we propose a mortar element method with Lagrange multiplier for incompressible Stokes problem,i.e.,the matching constraints of velocity on mortar edges are expressed in terms of Lagrange multipliers.We also present P_1 noncon- forming element attached to the subdomains.By proving inf-sup condition,we derive optimal error estimates for velocity and pressure.Moreover,we obtain satisfactory approximation for normal derivatives of the velocity across the interfaces.

基于Lagrange插值的学习猴群算法求解折扣{0-1}背包问题

折扣{0-1}背包问题(D{0-1}KP)的目的是在不超过背包载重的前提下,使得装入背包的所有物品价值系数之和为最大。针对已有算法在求解规模大、复杂度高的D{0-1}KP时的求解精度低的问题,提出了Lagrange插值的学习猴群算法(LSTMA)。首先,在基本猴群算法的望过程中重新定义了视野长度;其次,在跳过程中引入了种群中最优的个体作为第二个支点,并调整搜索机制;最后,在跳过程之后引入Lagrange插值操作来提高算法的搜索性能。对四类实例的仿真结果表明:LSTMA在求解D{0-1}KP时的求解精度高于对比算法,并且具有良好的鲁棒性。

集-集映射向量极值问题的Lagrange乘子和鞍点定理

本文先建立了集－集映射的一个广义择一性定理．在目标为锥凸和满足 推广了的Ｓｌａｔｅｒ约束规格的条件下，我们利用本文的择一性定理，给出了集一集映射 向量极值问题关于锥－超极小解的Ｌａｇｒａｎｇｅ乘子定理和鞍点定理．

连续Φ-有界变差函数的Lagrange插值逼近

本文主要讨论连续 Φ-有界变差函数借助于 Jacobi多项式的根的 L agrange插值逼近问题 ,并给出了插值多项式在 [- 1,1]上一致收敛的速度估计 .

集值优化ε-严有效解的Lagrange型最优性条件

在Hausdorff局部凸拓扑线性空间中考虑集值优化的ε-严有效性,当目标函数和约束函数构成的序偶映射是近似锥-次类凸时,在较弱的约束品性假设下,借助凸集分离定理得到了集值优化ε-严有效解的Lagrange型最优性条件.

Fredholm积分-微分方程的高精度数值方法研究

研究积分项包含未知函数导数的Fredholm积分-微分方程的重心插值配点法.首先,利用重心Lagrange插值配点法和重心有理插值配点法构造Fredholm积分-微分方程的数值格式.其次,分别选取等距节点和第二类Chebyshev节点进行数值计算,并对两种插值法在不同节点下的精度进行比较.数值算例结果表明,两种插值配点法都可以得到较高的计算精度,但一般情况下为了得到高精度的数值解,优先采用重心Lagrange插值配点法在第二类Chebyshev节点上计算.

The Hamiltonian Canonical Form for Euler-Lagrange Equations

Based on the theory of calculus of variation, some suffcient conditions are given for some Euler-Lagrangcequations to be equivalently represented by finite or even infinite many Hamiltonian canonical equations. Meanwhile,some further applications for equations such as the KdV equation, MKdV equation, the general linear Euler Lagrangeequation and the cylindric shell equations are given.

A New Lagrangian Multiplier Method on Constrained Optimization

In this paper, a new augmented Lagrangian function with 4-piecewise linear NCP function is introduced for solving nonlinear programming problems with equality constrained and inequality constrained. It is proved that a solution of the original constrained problem and corresponding values of Lagrange multipliers can be found by solving an unconstrained minimization of the augmented Lagrange function. Meanwhile, a new Lagrangian multiplier method corresponding with new augmented Lagrangian function is proposed. And this method is implementable and convergent.

用第一类Lagrange方程求解平面多体系统约束力的方法

利用第一类Lagrange方程建立多体系统的动力学方程时,系统的约束力是与Lagrange乘子有关的函数。该文采用笛卡儿坐标和建立约束方程的局部方法,给出了一种求解多体系统约束力的方法。该方法可使固定支承面的法向约束力及铰链约束力在惯性坐标轴上的投影与Lagrange乘子一一对应,从而便于系统约束力的分析和求解,最后用算例验证了该方法的正确性。

Lagrange乘子初始值和罚因子迭代方式的研究

以Ｒｏｃｋａｆｅｌｌａｒ乘子罚函数作为基准，利用Ｍａｔｌａｂ强大的数值计算功能，通过数值试验，对Ｌａｇｒａｎｇｅ乘子初始值和罚因子迭代方式进行了研究，比较了不同的乘子初始值和罚因子迭代序列对算法效率的影响，为大规模优化算法的研究提供了有益的借鉴．

采用结构进化策略的Lagrange乘子法优化换热网络

针对罚函数法处理有约束问题时存在的不足,采用Lagrange乘子法优化换热网络。为求解Lagrange函数方程组,根据确定性方法,提出最速下降法求解策略以及Powell法求解策略。通过极小值判断机制,保证Lagrange函数方程组的解是原换热网络目标函数值的极小值。根据实际工况,提出结构进化策略,与Lagrange乘子法相结合,实现了换热网络全局最优化。通过经典算例验证了两种求解策略的有效性、准确性以及结构进化策略的通用性。与文献结果进行对比,结果表明本算法具有较强的局部搜索能力以及全局搜索能力,能够找到更优的换热网络结构,有利于在工业生产中节约成本。