A column generation approach for solving the patient admission scheduling problem

This paper addresses the Patient Admission Scheduling (PAS) problem. The PAS problem entails assigning elective patients to beds, while satisfying a number of hard constraints and as many soft constraints as is possible, and arises at all planning levels for hospital management. There exist a few, different variants of this problem. In this paper we consider one such variant and propose an optimization-based heuristic building on branch-and-bound, column generation, and dynamic constraint aggregation to solve it. We achieve tighter lower bounds than previously reported in the literature and, in addition, we are able to produce new best known solutions for five out of twelve instances from a publicly available repository.     

Aggregation of Malmquist productivity indexes allowing for reallocation of resources

In this paper we consider aggregate Malmquist productivity index measures which allow inputs to be reallocated within the group (when in output orientation). This merges the single period aggregation results allowing input reallocation of Nesterenko and Zelenyuk (2007) with the aggregate Malmquist productivity index results of Zelenyuk (2006) to determine aggregate Malmquist productivity indexes that are justified by economic theory, consistent with previous aggregation results, and which maintain analogous decompositions to the original measures. Such measures are of direct relevance to firms or countries who have merged (making input reallocation possible), allowing them to measure potential productivity gains and how these have been realised (or not) over time.     

Shrinking and boundedly complete Schauder frames in Fréchet spaces

We study Schauder frames in Fréchet spaces and their duals, as well as perturbation results. We define shrinking and boundedly complete Schauder frames on a locally convex space, study the duality of these two concepts and their relation with the reflexivity of the space. We characterize when an unconditional Schauder frame is shrinking or boundedly complete in terms of properties of the space. Several examples of concrete Schauder frames in function spaces are also presented.     

Optimal reinsurance and investment strategies for insurer under interest rate and inflation risks

In this paper, we investigate an optimal reinsurance and investment problem for an insurer whose surplus process is approximated by a drifted Brownian motion. Proportional reinsurance is to hedge the risk of insurance. Interest rate risk and inflation risk are considered. We suppose that the instantaneous nominal interest rate follows an Ornstein–Uhlenbeck process, and the inflation index is given by a generalized Fisher equation. To make the market complete, zero-coupon bonds and Treasury Inflation Protected Securities (TIPS) are included in the market. The financial market consists of cash, zero-coupon bond, TIPS and stock. We employ the stochastic dynamic programming to derive the closed-forms of the optimal reinsurance and investment strategies as well as the optimal utility function under the constant relative risk aversion (CRRA) utility maximization. Sensitivity analysis is given to show the economic behavior of the optimal strategies and optimal utility.     

从几何的角度看微分中值定理

从平面几何中曲线之间的相切关系不依赖于坐标轴的选取这一基本事实去看数学分析中Rolle中值定理、Lagrange中值定理以及Cauchy中值定理.     

Discrete-space partial dynamic equations on time scales and applications to stochastic processes

We consider a general class of discrete-space linear partial dynamic equations. The basic properties of solutions are provided (existence and uniqueness, sign preservation, maximum principle). Above all, we derive the following main results: first, we prove that the solutions depend continuously on the choice of the time scale. Second, we show that, under certain conditions, the solutions describe probability distributions of nonhomogeneous Markov processes, and that their time integrals remain the same for all underlying regular time scales.     

基于核的区间直觉模糊信息集成的一类算子及其决策应用

定义了区间数核、区间直觉模糊数核的概念.并以此为基础,提出了区间直觉模糊数表示的模糊信息的几个集成算子:IIFKWA,IIFKWG,IIFKOWA IIFKOWG,IIFKHA,IIFKHG,研究了算子性质.探讨了集成算子在多属性决策中的应用,算例分析表明其具有可行性与有效性.     

L~2(R~n)中MRA Parseval框架小波和它们的乘子

刻画了L~2(R~n)中具有扩展矩阵伸缩的广义低通滤波器和多尺度分析Parseval框架小波(缩写为MRA PFW).首先,研究了伪逆的尺度函数、广义的低通滤波器和MRA PFW,给出它们的一些刻画.接着,我们给出与MRA PFW相联系的几类乘子的一些刻画.最后,给出了一个例子来证明的结论.     

基于RS和SVM的动态供应链成员选择算法

良好的成员选择方法是动态供应链平稳运行的重要基础,针对动态供应链成员选择时面临决策属性多且可供决策分析数据样本少的难题,提出了基于粗糙集和支持向量机的动态供应链成员选择算法,核心是应用粗糙集进行属性约简,然后结合支持向量机进行链上成员分类.方法在保证不会降低分类性能的前提下,达到降低数据维数和分类过程中复杂度的目的.     

带有分批费用的容量有界的单机平行分批排序问题

考虑的问题是在添加工资费用或包装费用等附加的分批费用下,如何使单机平行分批中总完工时间和分批费用之和达到最小.首先我们假定工件和批处理机都在零时刻到达,工件被成批地进行加工,一旦开始加工就不允许中断,每批的加工时间等于该批中最大的加工时间,而且假设每分一批都产生一个分批费用.然后对具有m个不同的加工时间,批容量有界且为固定值b的情形下目标函数为∑C_j与分批费用之和这一排序问题,利用动态规划的方法给出了多项式时间算法,时间界为O(b²m2m²222^m).