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根据广义乘子法的思想,将具有等式约束和非负约束的凸二次规划问题转化只有非负约束的简单凸二次规划,通过简单凸二次规划来得到解等式约束一非负约束的凸二次规划新算法,新算法不用求逆矩阵,这样可充分保持矩阵的稀疏性,用来解大规模稀疏问题,数值结果表明:在微机486/33上就能解较大规模的凸二次规划。 相似文献
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部分变量带非负约束的严格凸二次规划问题的新算法 总被引:1,自引:0,他引:1
本将正交校正共轭梯度法推广来解只有部分变量带非负约束而其它变量无约束的严格凸二次规划,所建立的新算法的优点是:在迭代过程中,不用求逆矩阵,这样能保持矩阵的稀疏性,数值结果表明,算法对大规模稀疏二次规划问题是可行和有效的。 相似文献
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本文将正交校正共轭梯度法推广来解只有部分变量带非负约束而其它变量无约束的严格凸二次规划,所建立的新算法的优点是:在迭代过程中,不用求逆矩阵,这样能保持矩阵的稀疏性,数值结果表明:算法对大规模稀疏二次规划问题是可行和有效的. 相似文献
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非负正交约束优化问题是同时带有非负约束和正交约束的优化问题,该类问题在机器学习和数据科学中有着重要的应用。常见的非负正交约束优化问题包括二次指派问题、图匹配问题、非负正交矩阵分解问题、非负主成分分析和K-指示模型等。由于非负约束和正交约束的共同作用,该类问题具有一定的组合结构,一般是NP-难的。本文主要介绍非负正交约束优化问题的基本理论性质、求解算法以及相关的应用模型。 相似文献
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An inverse problem of determination of a coefficient in an elliptic equation is considered. This problem is ill-posed in the sense of Hadamard and Tikhonov's regularization method is used for solving it in a stable way. This method requires globally solving nonconvex optimization problems, the solution methods for which have been very little studied in the inverse problems community. It is proved that the objective function of the corresponding optimization problem for our inverse problem can be represented as the difference of two convex functions (d.c. functions), and the difference of convex functions algorithm (DCA) in combination with a branch-and-bound technique can be used to globally solve it. Numerical examples are presented which show the efficiency of the method. 相似文献
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本文针对传统的基于边的最小支撑树逆问题,提出了一类基于点边更新策略的最小支撑树逆问题.更新一个点是指减少与此点相关联的某些边的权值.根据是否含有更新点的费用,考虑了两类模型,它们均可转化为森林上的最小(费用)点覆盖的求解问题,算法的复杂性都是O(mn),其中m=|E|n=|V|。 相似文献
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In this paper we are concerned with a special class of bicriterion path problems. For the considered class of bicriterion problems at least one of the objectives is type MAXMIN. For the other one, besides an objective type MAXMIN also a MINSUM and a MINRATIO type objective are considered. Two algorithms are presented for the considered class of bicriterion path problems. The first one only determines the minimal complete set of nondominated paths and the second one determines the entire set of nondominated paths. Both algorithms can be used for any type of bicriterion path problems, since one of the objectives is type MAXMIN and an algorithm exists to determine the best path for the other objective. Computational statistics for the three types of considered bicriterion path problems are also presented. 相似文献
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《Mathematical and Computer Modelling》2007,45(3-4):270-280
Direct and inverse dynamic problems for the equation of SH-waves in porous media are considered. A singular solution of the direct dynamic problem is constructed. A system of nonlinear Volterra integral equations of the second kind is obtained for the dynamic inverse problems in question. Theorems of uniqueness and theorems of existence in the small for the considered inverse problems are proved. Also, theorems of continuous dependence of solutions of inverse dynamic problems on input data are proved. 相似文献
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We propose a generalization of the inverse problem which we will call the adjustment problem. For an optimization problem with linear objective function and its restriction defined by a given subset of feasible solutions, the adjustment problem consists in finding the least costly perturbations of the original objective function coefficients, which guarantee that an optimal solution of the perturbed problem is also feasible for the considered restriction. We describe a method of solving the adjustment problem for continuous linear programming problems when variables in the restriction are required to be binary. 相似文献
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带有随机因素的逆DEA模型 总被引:3,自引:0,他引:3
韩松 《数学的实践与认识》2003,33(3):23-29
本文讨论含有随机因素的逆 DEA模型 .逆 DEA模型解决的问题是 :对于某个决策单元 (DMU ) ,若增加其输入 ,在保持相对效率水平不变的情况下 ,估计 (预测 )输出应增加多少 .因此逆 DEA模型可用于短期预测问题 .带有随机因素的逆 DEA模型 ,是将该问题转化成机会约束的多目标规划问题 ,在某些特殊情况下 ,成为机会约束的线性规划问题 . 相似文献
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This paper considers the following inverse optimization problem: given a linear program, a desired optimal objective value, and a set of feasible cost vectors, determine a cost vector such that the corresponding optimal objective value of the linear program is closest to the desired value. The above problem, referred here as the inverse optimal value problem, is significantly different from standard inverse optimization problems that involve determining a cost vector for a linear program such that a pre-specified solution vector is optimal. In this paper, we show that the inverse optimal value problem is NP-hard in general. We identify conditions under which the problem reduces to a concave maximization or a concave minimization problem. We provide sufficient conditions under which the associated concave minimization problem and, correspondingly, the inverse optimal value problem is polynomially solvable. For the case when the set of feasible cost vectors is polyhedral, we describe an algorithm for the inverse optimal value problem based on solving linear and bilinear programming problems. Some preliminary computational experience is reported.Mathematics Subject Classification (1999):49N45, 90C05, 90C25, 90C26, 90C31, 90C60Acknowledgement This research has been supported in part by the National Science Foundation under CAREER Award DMII-0133943. The authors thank two anonymous reviewers for valuable comments. 相似文献
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A. M. Denisov 《Computational Mathematics and Mathematical Physics》2013,53(5):580-587
Two inverse problems for a hyperbolic equation with a small parameter multiplying the highest derivative are considered. The existence and uniqueness of their solutions are proved. As the small parameter tends to zero, the solutions of the inverse problems are proved to converge to solutions of inverse problems for a parabolic equation. 相似文献
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A version of the simplex method for solving stochastic linear control problems is presented. The method uses a compact basis inverse representation that extensively exploits the original problem data and takes advantage of the supersparse structure of the problem. Computational experience indicates that the method is capable of solving large problems.This research was supported by Programs CPBP02.15 and RPI.02. 相似文献