搜索结果: 151-165 共查到“知识库 运筹学”相关记录1007条 . 查询时间(2.403 秒)
研究Stein-Stein随机波动率模型下带动态VaR约束的最优投资组合选择问题. 假设投资者的目标是最大化终端财富的期望幂效用,可投资于无风险资产和一种风险资产, 风险资产的价格过程由Stein-Stein随机波动率模型刻画. 同时, 投资者期望能在投资过程中利用动态VaR约束控制所面对的风险.运用Bellman动态规划方法和Lagrange乘子法, 得到了该约束问题最优策略的解析式及特殊情形下...
对不等式约束优化问题提出了一个低阶精确罚函数的光滑化算法. 首先给出了光滑罚问题、非光滑罚问题及原问题的目标函数值之间的误差估计，进而在弱的假
设之下证明了光滑罚问题的全局最优解是原问题的近似全局最优解. 最后给出了一个基于光滑罚函数的求解原问题的算法，证明了算法的收敛性，并给出数值算例说明算法的可行性.
基于CAR-DEA方法的环境效率评价研究
数据包络分析 不期望产出 保证域 CAR-DEA
2012/8/3
现有环境效率评价的DEA方法没有考虑多维偏好约束问题，即不同决策单元对不同期望产出和不期望产出的偏好不同. 以地区为例，不同地区对GDP、废水和废气赋予的权重偏好各不相同. 在这种情况下，由于各决策单元的偏好约束不同，形成多维偏好约束集，在传统DEA模型中容易出现无可行解现象. 针对这一问题，基于CAR-DEA方法，结合保证域理论，提出一种解决多维偏好约束集问题的环境效率评价模型. 采用中国工业系...
可达到和可逼近总极小点的存在性和最优性
总极值问题 丰满极小点 拟上半丰满 变差积分
2012/8/3
针对积分总极值，讨论并拓展了丰满集和丰满函数的概念，研究了拟上丰满和伪上丰满函数的总极值问题. 在总极值的变差积分最优性条件下，证明了拟上丰满函数的可达到极小点和伪上丰满函数的可逼近极小点的存在性.
对于一个简单图G, 方阵Q(G)=D(G)+A(G)称为G的无符号拉普拉斯矩阵,其中D(G)和A(G)分别为G的度对角矩阵和邻接矩阵. 一个图是Q整图是指该图的无符号拉普拉斯矩阵的特征值全部为整数.首先通过Stanic 得到的六个顶点数目较小的Q整图，构造出了六类具有无穷多个的非正则的Q整图. 进而,通过图的笛卡尔积运算得到了很多的Q整图类. 最后, 得到了一些正则的Q整图.
基于二次函数光滑化逼近的修正低阶罚函数
修正罚函数 光滑化逼近 低阶罚函数 不等式约束优化问题
2012/8/3
针对不等式约束优化问题, 给出了通过二次函数对低阶精确罚函数进行光滑化逼近的两种函数形式, 得到修正的光滑罚函数. 证明了在一定条件下, 当罚参数充分大, 修正的光滑罚问题的全局最优解是原优化问题的全局最优解. 给出的两个数值例子说明了所提出的光滑化方法的有效性.
研究一种称为次~$b$ 凸函数的广义凸函数, 并介绍了次~$b$ 凸集的概念. 分别在一般情形及可微情形下讨论了次~$b$ 凸函数的相关性质, 得到了次~$b$ 凸函数成为拟凸函数及伪凸函数的充分条件. 最后, 在次~$b$ 凸函数的条件下给出了无约束及带不等式约束规划的最优性条件.
针对战时多阶段备件需求的不确定性及阶段相关性特点,提出了基于模糊推理的战时备件需求预测方法。把体现作战意图的专家预测值与体现需求量阶段相关性的Markov 预测值结合起来,通过Mamdani 模糊推理规则及反模糊化给出最终备件需求预测值。采用语言变量描述备件需求量,定义了需求量模糊集合,并在Markov 预测需求量时直接采用该模糊集描述系统状态。实例表明该预测方法能有效用于缺乏历史需求记录的战时备...
Restricted normal cones and sparsity optimization with affine constraints
Compressed sensing constraint qualification Friedrichs angle linear convergence
2012/5/24
The problem of finding a vector with the fewest nonzero elements that satisfies an underdetermined system of linear equations is an NP-complete problem that is typically solved numerically via convex ...
Convex dwell-time characterizations for uncertain linear impulsive systems
Impulsive systems dwell-time looped-functionals stability robustness
2012/5/9
New sufficient conditions for the characterization of dwell-times for linear impulsive systems are proposed and shown to coincide with continuous decrease conditions of a certain class of looped-funct...
Approximation Bounds for Sparse Principal Component Analysis
Sparse PCA convex relaxation semidefinite programming approximation bounds detection
2012/5/9
We produce approximation bounds on a semidefinite programming relaxation for sparse principal component analysis. These bounds control approximation ratios for tractable statistics in hypothesis testi...
Alternatives for optimization in systems and control: convex and non-convex approaches
optimization methods systems and control convex VS non-convex
2012/5/9
In this presentation, we will develop a short overview of main trends of optimization in systems and control, and from there outline some new perspectives emerging today. More specifically, we will fo...
On the dynamic programming principle for uniformly nondegenerate stochastic differential games in domains and the Isaacs equations
Dynamic programming principle stochastic games Isaacs equation
2012/5/9
We prove the dynamic programming principe for uniformly nondegenerate stochastic differential games in the framework of time-homogeneous diffusion processes considered up to the first exit time from a...
On the dynamic programming principle for uniformly nondegenerate stochastic differential games in domains
Dynamic programming principle stochastic games Isaacs equation
2012/5/9
We prove the dynamic programming principe for uniformly nondegenerate stochastic differential games in the framework of time-homogeneous diffusion processes considered up to the first exit time from a...
Hyperbolicity cones of elementary symmetric polynomials are spectrahedral
hyperbolic polynomials hyperbolicity cones spectrahedral cones elementary symmetric polynomials spanning trees matrix-tree theorem
2012/4/16
We prove that the hyperbolicity cones of elementary symmetric polynomials are spectrahedral, i.e., they are slices of the cone of positive semidefinite matrices. The proof uses the matrix--tree theore...