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1.
作者介绍了一种基于向量值延拓函数的广义增广拉格朗日函数,建立了基于广义增广拉格朗日函数的集值广义增广拉格朗日对偶映射和相应的对偶问题,得到了相应的强对偶和弱对偶结果,将所获结果应用到约束向量优化问题.该文的结果推广了一些已有的结论.  相似文献   

2.
建立了与多目标规划问题等价的η-近似多目标规划问题;对η-近似多目标规划问题引入η-拉格朗日函数和η-鞍点,并给出了η-鞍点与原多目标规划问题有效解之间的关系。  相似文献   

3.
本文研究了均值-方差优化准则下,保险人的最优投资和最优再保险问题.我们用一个复合泊松过程模型来拟合保险人的风险过程,保险人可以投资无风险资产和价格服从跳跃-扩散过程的风险资产.此外保险人还可以购买新的业务(如再保险).本文的限制条件为投资和再保险策略均非负,即不允许卖空风险资产,且再保险的比例系数非负.除此之外,本文还引入了新巴塞尔协议对风险资产进行监管,使用随机二次线性(linear-quadratic,LQ)控制理论推导出最优值和最优策略.对应的哈密顿-雅克比-贝尔曼(Hamilton-Jacobi-Bellman,HJB)方程不再有古典解.在粘性解的框架下,我们给出了新的验证定理,并得到有效策略(最优投资策略和最优再保险策略)的显式解和有效前沿.  相似文献   

4.
本文引入一类新的具有弱零极值性质的非线性增广罚函数,并利用增广拉格朗日方法和抽象共轭与双共轭,抽象次梯度,原问题稳定等概念来研究Banach空间中集值向量优化问题的非线性增广拉格朗日对偶定理·若原问题是稳定的,则原问题与对偶问题之间存在零对偶间隙。在下确界外稳定的假设下得到零对偶间隙性质成立的充分必要条件.这些结论是有限维空间上的实值优化问题和集值向量优化问题中相应结论的推广.  相似文献   

5.
求解无容量设施选址问题的半拉格朗日松弛新方法   总被引:1,自引:0,他引:1  
无容量设施选址问题(un-capacitated facility location,UFL)是应用于诸多领域的经典组合优化难题,半拉格朗日松弛方法是求解UFL问题的一种精确方法.分析了半拉格朗日松弛方法在求解UFL问题时所具有的性质,在此基础上,对求解UFL问题的半拉格朗日松弛方法进行了一定的理论完善,并探讨了提高半拉格朗日松弛方法求解性能的有效途径.数值计算结果表明:改进方法具有明显的可行性和有效性.  相似文献   

6.
该文讨论局部凸空间中的约束集值优化问题. 首先, 在生成锥内部凸-锥-类凸假设下, 建立了Henig真有效解在标量化和Lagrange乘子意义下的最优性条件. 其次, 对集值Lagrange映射引入Henig真鞍点的概念, 并用这一概念刻画了Henig真有效解. 最后, 引入了一个标量Lagrange对偶模型, 并得到了关于Henig真有效解的对偶定理. 另外, 该文所得结果均不需要约束序锥有非空的内部.  相似文献   

7.
罗葵  周旋  赵洪雅  王思敏 《数学杂志》2015,35(1):167-172
本文研究了幂效用函数下带有比例保本约束的最优投资组合选择问题.利用拉格朗日乘子和投资组合复制方法,得到最优财富过程和最优投资组合,推广了带有限制的投资组合的相关结果.  相似文献   

8.
首先引入非线性问题稳定性的统一模式,其次给出拉格朗日微分中值问题的有限理性模型,最后研究拉格朗日微分中值问题解的稳定性.通过验证假设的条件和利用已有的结论,得到大多数的拉格朗日微分中值问题都是结构稳定的和鲁棒的.  相似文献   

9.
以过去的信息为条件,以一致性风险度量CVaR为优化目标,以组合收益率为约束条件,建立了时变投资组合优化模型,通过基于pair-copula-GARCH模型的蒙特卡洛模拟方法得到未来某时刻收益率的多个可能情景,并引入一个特殊函数实现了投资组合模型的线性化,得到了最优投资组合策略.最后针对提出的模型进行了实例分析.  相似文献   

10.
Markowitz首先采用方差度量风险,并应用于投资组合优化中,大多数的均值方差模型仅对随机投资组合优化或模糊投资组合优化进行研究,然而,实际投资组合优化问题既包含随机信息也包含模糊信息。本文首先定义随机模糊变量的方差,并用其度量风险,提出了具有交易成本、借贷约束和阀值约束的均值-方差随机模糊投资组合优化模型。基于随机模糊理论,将上述模型转化为具有线性等式和线性不等式约束的凸二次规划问题,并得到其KKT条件。本文还提出改进的旋转算法求解上述模型,该算法消掉KKT条件中部分变量,减少计算量。最后,采用中国证券市场的实际数据进行样本内分析和样本外分析,验证了上述模型和算法的有效性。  相似文献   

11.
$k$-均值问题是机器学习和组合优化领域十分重要的问题。它是经典的NP-难问题, 被广泛的应用于数据挖掘、企业生产决策、图像处理、生物医疗科技等领域。随着时代的发展, 人们越来越注重于个人的隐私保护:在决策通常由人工智能算法做出的情况下, 如何保证尽可能多地从数据中挖掘更多信息,同时不泄露个人隐私。近十年来不断有专家学者研究探索带隐私保护的$k$-均值问题, 得到了许多具有理论指导意义和实际应用价值的结果, 本文主要介绍关于$k$-均值问题的差分隐私算法供读者参考。  相似文献   

12.
A parametric convex programming problem with an operator equality constraint and a finite set of functional inequality constraints is considered in a Hilbert space. The instability of this problem and, as a consequence, the instability of the classical Lagrange principle for it is closely related to its regularity and the subdifferentiability properties of the value function in the optimization problem. A sequential Lagrange principle in nondifferential form is proved for the indicated convex programming problem. The principle is stable with respect to errors in the initial data and covers the normal, regular, and abnormal cases of the problem and the case where the classical Lagrange principle does not hold. It is shown that the classical Lagrange principle in this problem can be naturally treated as a limiting variant of its stable sequential counterpart. The possibility of using the stable sequential Lagrange principle for directly solving unstable optimal control problems and inverse problems is discussed. For two illustrative problems of these kinds, the corresponding stable Lagrange principles are formulated in sequential form.  相似文献   

13.
In this paper,a semiparametric two-sample density ratio model is considered and the empirical likelihood method is applied to obtain the parameters estimation.A commonly occurring problem in computing is that the empirical likelihood function may be a concaveconvex function.Here a simple Lagrange saddle point algorithm is presented for computing the saddle point of the empirical likelihood function when the Lagrange multiplier has no explicit solution.So we can obtain the maximum empirical likelihood estimation (MELE) of parameters.Monte Carlo simulations are presented to illustrate the Lagrange saddle point algorithm.  相似文献   

14.
We consider a linear time-optimal problem in which initial state values depend on a parameter and study the problem of the solution structure identification for small parameter perturbations. Properties of the time-optimal function and a point-set mapping, defined by optimal Lagrange vectors, are studied as well as the dependence of the solution on the parameter. Special attention is paid to the solution properties in irregular points.  相似文献   

15.
In this paper,a semiparametric two-sample density ratio model is considered and the empirical likelihood method is applied to obtain the parameters estimation.A commonly occurring problem in computing is that the empirical likelihood function may be a concaveconvex function.Here a simple Lagrange saddle point algorithm is presented for computing the saddle point of the empirical likelihood function when the Lagrange multiplier has no explicit solution.So we can obtain the maximum empirical likelihood estimation (MELE) of parameters.Monte Carlo simulations are presented to illustrate the Lagrange saddle point algorithm.  相似文献   

16.
A new method is used for solving nonlinear multiobjective fractional programming problems having V-invex objective and constraint functions with respect to the same function η. In this approach, an equivalent vector programming problem is constructed by a modification of the objective fractional function in the original nonlinear multiobjective fractional problem. Furthermore, a modified Lagrange function is introduced for a constructed vector optimization problem. By the help of the modified Lagrange function, saddle point results are presented for the original nonlinear fractional programming problem with several ratios. Finally, a Mond-Weir type dual is associated, and weak, strong and converse duality results are established by using the introduced method with a modified function. To obtain these duality results between the original multiobjective fractional programming problem and its original Mond-Weir duals, a modified Mond-Weir vector dual problem with a modified objective function is constructed.  相似文献   

17.
Characterizations of optimal solution sets of convex infinite programs   总被引:1,自引:0,他引:1  
T. Q. Son  N. Dinh 《TOP》2008,16(1):147-163
In this paper, several Lagrange multiplier characterizations of the solution set of a convex infinite programming problem are given. Characterizations of solution sets of cone-constrained convex programs are derived as well. The procedure is then adopted to a semi-convex problem with convex constraints. For this problem, we present firstly a necessary and sufficient condition for optimality and secondly a characterization of its optimal solution set, based on a Lagrange multiplier associated with a given solution and on directional derivatives of the objective function.   相似文献   

18.
A convex programming problem in a Hilbert space with an operator equality constraint and a finite number of functional inequality constraints is considered. All constraints involve parameters. The close relation of the instability of this problem and, hence, the instability of the classical Lagrange principle for it to its regularity properties and the subdifferentiability of the value function in the problem is discussed. An iterative nondifferential Lagrange principle with a stopping rule is proved for the indicated problem. The principle is stable with respect to errors in the initial data and covers the normal, regular, and abnormal cases of the problem and the case where the classical Lagrange principle does not hold. The possibility of using the stable sequential Lagrange principle for directly solving unstable optimization problems is discussed. The capabilities of this principle are illustrated by numerically solving the classical ill-posed problem of finding the normal solution of a Fredholm integral equation of the first kind.  相似文献   

19.
增广Lagrange方法是求解非线性规划的一种有效方法.从一新的角度证明不等式约束非线性非光滑凸优化问题的增广Lagrange方法的收敛性.用常步长梯度法的收敛性定理证明基于增广Lagrange函数的对偶问题的常步长梯度方法的收敛性,由此得到增广Lagrange方法乘子迭代的全局收敛性.  相似文献   

20.
Lagrange基函数的复矩阵有理插值及连分式插值   总被引:1,自引:0,他引:1  
1引言 矩阵有理插值问题与系统线性理论中的模型简化问题和部分实现问题有着紧密的联系~[1][2],在矩阵外推方法中也常常涉及线性或有理矩阵插值问题~[3]。按照文~[1]的阐述。目前已经研究的矩阵有理插值问题包括矩阵幂级数和Newton-Pade逼近。Hade逼近,联立Pade逼近,M-Pade逼近,多点Pade逼近等。显然,上述各种形式的矩阵Pade逼上梁山近是矩  相似文献   

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