基于投入产出分析的燃料乙醇价格变动模拟研究

目前我国的燃料乙醇定价机制不能真实反映出燃料乙醇原料的价格变动对燃料乙醇价格的实际影响.该文编制了2005年中国燃料乙醇投入产出表,在此基础上,建立了燃料乙醇价格影响模型,接着运用M ATLAB软件,模拟了生产燃料乙醇的原料——玉米的价格变动时及玉米和水、电等资源性产品的价格同时变动时对燃料乙醇价格的实际影响.     

影子价格及其在资源配置中的应用研究

为了应用影子价格实现资源在全社会的最优配置,本文通过线性规划的对偶理论和非线性优化问题的Kuhn-Tucker条件揭示了影子价格的本质,在资源配置优化问题中线性规划模型中的影子价格就是其对偶问题的最优解,非线性规划模型中的影子价格就是与最优解相对应的拉格朗日乘数。根据松紧定理解释了资源影子价格与资源限量之间的关系,还对线性规划模型与非线性规划模型中影子价格的不同表现进行了分析。最后阐明了影子价格在资源配置中的应用。     

疫情环境下价格导向的防护物资最优生产分配机制研究

新型冠状病毒疫情导致防护物资匮乏,增加了医护人员受感染的风险.现构建了防护物资最优生产-分配-定价模型,并在此基础上提出了广义影子价格的概念,以此作为防护物资定价的参考和依据,通过价格引导生产型企业合理扩大生产规模,以解决当前防护物资短缺的困难.广义影子价格反映了企业产能提升成本等因素,相比传统影子价格更适用于为防护物资统一定价.另外,利用广义影子价格与拉格朗日乘子集合之间的联系,提出了一个线性规划模型用以计算广义影子价格.数值仿真结果说明了广义影子价格在防护物资定价上的适用性.     

疫情环境下价格导向的防护物资最优生产分配机制研究

新型冠状病毒疫情导致防护物资短缺,增加了医护人员受感染的风险.现构建了防护物资最优生产-分配-定价模型,并在此基础上提出了广义影子价格的概念,以此作为防护物资定价的参考和依据,通过价格引导生产型企业合理扩大生产规模,以解决当前防护物资短缺的困难.广义影子价格反映了企业产能提升成本等因素,相比传统影子价格更适用于为防护物资统一定价.另外,利用广义影子价格与拉格朗日乘子集合之间的联系,提出了一个线性规划模型用以计算广义影子价格.数值仿真结果说明了广义影子价格在防护物资定价上的适用性.     

影子价格与影子成本

本文根据线性规划问题对偶变量和影子价格的经济意义,给出了影子成本的概念,讨论了影子成本与对偶价格的关系.通过灵敏度分析给出了影子成本的动态表示,并进一步阐明了影子价格和影子成本的惟一性以及影子成本在经济管理中的应用.     

线性规划消耗系数矩阵灵敏度分析的某些探讨

讨论了线性规划模型中 ,消耗系数矩阵 A中某个基变量或某个约束方程的系数向量变化以及增减约束方程时 ,对最优基、最优解、目标函数值和影子价格的影响 .     

多种资源灵敏度分析和影子价格的探讨

本在原有的线性规划灵敏度分析和影子价格理论的基础上，讨论了多种资源变化的灵敏度分析中影子价格的调节作用，提出资源最佳数量的LP模型，指出在多种资源变化的情况下，影子价格的应用可以而且应该超越传统的观点，以统筹调配各种资源，追求总的目标函数值达到最优。     

影子价格与企业管理决策

本文利用线性规划与非线性规划模型，讨论了目标函数增量，影子价格及相应的常数项增量的特征区间之间的关系，从理论上对文[1]、[2]、[3]中的问题作出了解释。我们还给出了线性规划与非线性规划发生悖论的充要条件，对文[5]、[7]中的结果进行了推广。     

线性规划影子价格的求解判断方法探讨

针对线性规划对偶问题最优解不唯一时,在已有文献提出的对偶最优解不唯一的充要条件定理基础上,结合线性规划灵敏度分析,提出影子价格的求解判断的简单准则及其命题,并进行证明.最后,用算例加以分析,指出该判断方法简单易行,也可作为通过计算软件求解影子价格的准确判断方法.     

最优化方法与影子价格──再谈数学与经济

本文给出了影子价格严格的数学定义，并根据定义用四个定理严格证明了在线性规划，二次规划、非线性规划中影子价格的计算公式。然后，从资源原采购、资源投向，投资方向和科学确定商品的地区差价等方面，对影子价格的经济应用进行了实证分析。     

Fuzzy regression analysis using neural networks

In this paper, we propose simple but powerful methods for fuzzy regression analysis using neural networks. Since neural networks have high capability as an approximator of nonlinear mappings, the proposed methods can be applied to more complex systems than the existing LP based methods. First we propose learning algorithms of neural networks for determining a nonlinear interval model from the given input-output patterns. A nonlinear interval model whose outputs approximately include all the given patterns can be determined by two neural networks. Next we show two methods for deriving nonlinear fuzzy models from the interval model determined by the proposed algorithms. Nonlinear fuzzy models whose h-level sets approximately include all the given patterns can be derived. Last we show an application of the proposed methods to a real problem.     

目标规划在离散型动态投入产出模型中的应用

以离散型动态投入产出模型为约束条件的主体、以决策部门所希望达到的种种目标为约束条件的附加部分,建立动态投入产出目标规划模型.通过求解动态投入产出目标规划模型而得到离散型动态投入产出模型的解.此解法与其它解法相比具有更大的实用价值.     

基于随机微分博弈的动态投入产出问题研究

基于W Leontief提出的动态投入产出模型,讨论了考虑随机因素的离散时间下的最优策略设计问题.利用博弈论的思想,把动态投入产出系统抽象为离散时间的博弈模型,运用鞍点均衡策略设计出求解该投入产出问题的新方法,为宏观经济决策提供依据.     

进口对国内价格的波及效应分析

全球化经济进程以及我国加入世贸组织推动我国对外贸易快速发展,经济高速发展带来对资源的消耗日益增长,使得进口产品量进一步扩大,国内经济系统受进口产品的影响加重.然而国际市场价格的波动,以及我国进口关税的变化,导致了进口产品价格波动.由于经济系统中各个产业部门相互关联,进口产品比例和进口产品价格的波动必然对国内各个产业的产品价格产生相应的波及效应.本文应用投入产出的分析方法,构建进口产品价格影响模型,应用1997年和2002年投入产出表,定量研究了进口产品价格的变动对各个产业部门价格变动的波及效应,并进行了进口价格变动的模拟.     

基于现金流量的虚拟企业协同增值评估模型研究

虚拟企业是个开放性的复杂系统,其本质是协调成员企业的管理,提高和协调其有序性以达到协调增值的目的.基于现金流,通过黑箱理论与投入产出模型分别建立了成员企业、虚拟企业以及信息共享下的虚拟企业价值评估模型,通过比较三者的差值评估虚拟企业的协同增值效应.     

Twenty years of linear programming based portfolio optimization

Markowitz formulated the portfolio optimization problem through two criteria: the expected return and the risk, as a measure of the variability of the return. The classical Markowitz model uses the variance as the risk measure and is a quadratic programming problem. Many attempts have been made to linearize the portfolio optimization problem. Several different risk measures have been proposed which are computationally attractive as (for discrete random variables) they give rise to linear programming (LP) problems. About twenty years ago, the mean absolute deviation (MAD) model drew a lot of attention resulting in much research and speeding up development of other LP models. Further, the LP models based on the conditional value at risk (CVaR) have a great impact on new developments in portfolio optimization during the first decade of the 21st century. The LP solvability may become relevant for real-life decisions when portfolios have to meet side constraints and take into account transaction costs or when large size instances have to be solved. In this paper we review the variety of LP solvable portfolio optimization models presented in the literature, the real features that have been modeled and the solution approaches to the resulting models, in most of the cases mixed integer linear programming (MILP) models. We also discuss the impact of the inclusion of the real features.     

Linear programming on a micro computer: An application in refinery modelling

Given the complexity of refinery modelling, linear programming for this application has until now been developed essentially on mainframes. New developments in microcomputer LP software now allow us to handle real life problems. This paper will describe the process of a general refinery, and how a micro based model has been designed to study its economics.     

In honour of professor Solomon G. Mikhlin on the occasion of his seventieth birthday

The system identification problem, within the context of this paper, is the determination of an input-output operator A based upon a limited amount of information. We consider the case where A is a linear, time invariant map on an appropriate function space and develop an algorithm for determining A from knowledge of input-output pairs in A.     

On solving the dual for portfolio selection by optimizing Conditional Value at Risk

This note is focused on computational efficiency of the portfolio selection models based on the Conditional Value at Risk (CVaR) risk measure. The CVaR measure represents the mean shortfall at a specified confidence level and its optimization may be expressed with a Linear Programming (LP) model. The corresponding portfolio selection models can be solved with general purpose LP solvers. However, in the case of more advanced simulation models employed for scenario generation one may get several thousands of scenarios. This may lead to the LP model with huge number of variables and constraints thus decreasing the computational efficiency of the model. To overcome this difficulty some alternative solution approaches are explored employing cutting planes or nondifferential optimization techniques among others. Without questioning importance and quality of the introduced methods we demonstrate much better performances of the simplex method when applied to appropriately rebuilt CVaR models taking advantages of the LP duality.