共查询到19条相似文献,搜索用时 62 毫秒
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求解简单界约束优化问题的一种逐次逼近法 总被引:1,自引:1,他引:0
马昌凤 《高等学校计算数学学报》1999,21(2):170-177
1引言考虑变量带简单界约束的非线性规划问题:其中二阶连续可微,a=(a1,a2,…,an),b=(b1,b2,…,bn),+i=1,2,…,n.问题(1)不仅是实际应用中出现的简单界约束最优化问题,而且相当一部分最优化问题可以把变量限制在有意义的区间内(参见[1]).因此无论在理论方面还是在实际应用方面,都有研究此类问题并给出简便而有效算法的必要.假设f是凸函数,记g(x)=f(x),则由K-T条件,问题(1)可化为求解下面的非光滑方程组:显然,(2)等价于易证,(3)等价于求解下面的非光滑方程… 相似文献
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边界约束非凸二次规划问题的分枝定界方法 总被引:2,自引:0,他引:2
本文是研究带有边界约束非凸二次规划问题,我们把球约束二次规划问题和线性约束凸二次规划问题作为子问题,分明引用了它们的一个求整体最优解的有效算法,我们提出几种定界的紧、松驰策略,给出了求解原问题整体最优解的分枝定界算法,并证明了该算法的收敛性,不同的定界组合就可以产生不同的分枝定界算法,最后我们简单讨论了一般有界凸域上非凸二次规划问题求整体最优解的分枝与定界思想。 相似文献
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一种解带补偿的随机规划的逼近方法 总被引:2,自引:0,他引:2
其中f(x)∈C~1且f(x)为凸函数,A∈IR~(m×n),x∈IR~n,b∈IR~m.(1)的一般形式可用可行方向法(Topkis-Veinott情形)得到一个Fritz-John点.但当f(x)或△f(x)太复杂以致难以计算时,此方法就不适当.为此考虑逼近问题: 相似文献
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用微分方程的解曲线确定约束优化问题的解即ODE方法已受到人们广泛重视和研究.潘平奇对无约束和带等式约束优化问题提出了很好的ODE方法.该方法的主要优点之一是没有扩大问题的规模.关于带不等式约束的优化问题的ODE方法,尚待研究.另外,虽然问题(1)可以通过标准化处理变成等式约束情形,再用[3]中的ODE方法求解,但这样做会扩大问题规模,因此,本文将在不扩大问题规模的基础上 相似文献
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当供应商的生产能力和销售商的需求量是随机参数时,建立了一类产品生产和运输成本问题的数学模型,它是一种随机优化模型.利用机会约束规划方法研究了在给定置信水平和其它相关约束条件时,此类随机优化问题的确定型等价式.给出了每个供应商给每个销售商的送货量,且达到了总运输成本最低.实际案例研究表明所建立的模型和求解方法有效,且分析了不同置信水平下最优值的变化,提供了选择最佳置信水平的方法. 相似文献
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Global Optimization Method for Solving Mathematical Programs with Linear Complementarity Constraints
N. V. Thoai Y. Yamamoto A. Yoshise 《Journal of Optimization Theory and Applications》2005,124(2):467-490
We propose a method for finding a global optimal solution of programs with linear complementarity constraints. This problem arises for instance in bilevel programming. The main idea of the method is to generate a sequence of points either ending at a global optimal solution within a finite number of iterations or converging to a global optimal solution. The construction of such sequence is based on branch-and-bound techniques, which have been used successfully in global optimization. Results on a numerical test of the algorithm are reported.The main part of this article was written during the first authors stay as Visiting Professor at the Institute of Policy and Planning Sciences, University of Tsukuba, Tsukuba, Japan. The second and the third authors were supported by Grant-in-Aid for Scientific Research C(2) 13650061 of the Ministry of Education, Culture, Sports, Science, and\break Technology of Japan.The authors thank P. B. Hermanns, Department of Mathematics, University of Trier, for carrying out the numerical test reported in Section 5. The authors also thank the referees and the Associate Editor for comments and suggestions which helped improving the first version of this article. 相似文献
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Interesting cutting plane approaches for solving certain difficult multiextremal global optimization problems can fail to converge. Examples include the concavity cut method for concave minimization and Ramana's recent outer approximation method for unary programs which are linear programming problems with an additional constraint requiring that an affine mapping becomes unary. For the latter problem class, new convergent outer approximation algorithms are proposed which are based on sufficiently deep l-norm or quadratic cuts. Implementable versions construct optimal simplicial inner approximations of Euclidean balls and of intersections of Euclidean balls with halfspaces, which are of general interest in computational convexity. Computational behavior of the algorithms depends crucially on the matrices involved in the unary condition. Potential applications to the global minimization of indefinite quadratic functions subject to indefinite quadratic constraints are shown to be practical only for very small problem sizes. 相似文献
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单调优化是指目标函数与约束函数均为单调函数的全局优化问题.本文提出一种新的凸化变换方法把单调函数化为凸函数,进而把单调优化问题化为等价的凸极大或凹极小问题,然后采用Hoffman的外逼近方法来求得问题的全局最优解.我们把这种凸化方法同Tuy的Polyblock外逼近方法作了比较,通过数值比较可以看出本文提出的凸化的方法在收敛速度上明显优于Polyblock方法. 相似文献
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Researchers first examined the problem of separable concave programming more than thirty years ago, making it one of the earliest branches of nonlinear programming to be explored. This paper proposes a new algorithm that finds the exact global minimum of this problem in a finite number of iterations. In addition to proving that our algorithm terminates finitely, the paper extends a guarantee of finiteness to all branch-and-bound algorithms for concave programming that (1) partition exhaustively using rectangular subdivisions and (2) branch on the incumbent solution when possible. The algorithm uses domain reduction techniques to accelerate convergence; it solves problems with as many as 100 nonlinear variables, 400 linear variables and 50 constraints in about five minutes on an IBM RS/6000 Power PC. An industrial application with 152 nonlinear variables, 593 linear variables, and 417 constraints is also solved in about ten minutes. 相似文献
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A Robust SQP Method for Mathematical Programs with Linear Complementarity Constraints 总被引:1,自引:0,他引:1
The relationship between the mathematical program with linear complementarity constraints (MPLCC) and its inequality relaxation
is studied. Based on this relationship, a new sequential quadratic programming (SQP) method is presented for solving the MPLCC.
A certain SQP technique is introduced to deal with the possible infeasibility of quadratic programming subproblems. Global
convergence results are derived without assuming the linear independence constraint qualification for MPEC, the nondegeneracy
condition, and any feasibility condition of the quadratic programming subproblems. Preliminary numerical results are reported.
Research is partially supported by Singapore-MIT Alliance and School of Business, National University of Singapore. 相似文献
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We consider a class of quadratic programs with linear complementarity constraints (QPLCC) which belong to mathematical programs
with equilibrium constraints (MPEC). We investigate various stationary conditions and present new and strong necessary and
sufficient conditions for global and local optimality. Furthermore, we propose a Newton-like method to find an M-stationary
point in finite steps without MEPC linear independence constraint qualification.
The research of this author is partially supported by NSERC, and Research Grand Council of Hong Kong. 相似文献
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H. P. Benson 《Journal of Optimization Theory and Applications》1998,98(1):17-35
Various difficulties arise in using decision set-based vector maximization methods to solve a multiple-objective linear programming problem (MOLP). Motivated by these difficulties, some researchers in recent years have begun to develop tools for analyzing and solving problem (MOLP) in outcome space, rather than in decision space. In this article, we present and validate a new hybrid vector maximization approach for solving problem (MOLP) in outcome space. The approach systematically integrates a simplicial partitioning technique into an outer approximation procedure to yield an algorithm that generates the set of all efficient extreme points in the outcome set of problem (MOLP) in a finite number of iterations. Some key potential practical and computational advantages of the approach are indicated. 相似文献
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本文提出了一类隐互补约束优化问题的磨光SQP算法.首先,我们给出了这类优化问题的最优性和约束规范性条件.然后,在适当假设条件下,我们证明了算法具有全局收敛性. 相似文献