“三角债”问题的图论模型

“三角债”是一种经济现象 ,它往往困扰着当事企业 ,使之一筹莫展 .本文提供清理三角债问题的一个数学模型 ,由于其结果的合理性和操作的简单性 ,因而具有可行性 ,可供有关部门在宏观调控中加以应用 .1　三角债问题的基本特征及处理原则如称欠债企业为“债户” ,被欠企业为“债     

贷款分配方法的数学模型及其解法

为了解决三角债问题，银行给出一笔贷款，应该如何分配这笔贷款，使清理的债务达到最大。本文建立这个问题的数学模型，并且给出一个解法。     

清理三角债问题的一种方法

本文给出了一种清理三角债问题中的资金分配方法，用以实现用有限的资金清理最大数额债务的目的．由于该法是在网络图上进行的，较之以往的方法具有直观、操作简单的优点．     

三角债清理的模型与算法

本文用图论和网络的观点研究了三角债问题，建立了解决三角债问题的网络模型，给出了为解决三角债所需投入的最少资金的计算公式及具体操作方法，这一研究无疑具有很强的理论意义和实际意义，所提供的算法也具有较好的可操作性。     

向量丛动力学系统研究注记（Ⅱ）—部份2

在这部份２中，我们行脱份１中叙述的定理３．１，这证明是通过换变 的办法，把原方程组化成微分动力系统理论中，有关典范方程组的一种形式一完成。然后用定理３．１加上预备定理２．１来证明部份１中宣布的本文主要定理。     

应重视万能公式的应用

大家知道不论a角的哪一种三角函数,都可以用万能公式把它化成tg a/2的有理式,这样就可以把问题转化为以tg a/2为变量的有理函数,往往有助于问题的解决。课本中指出了万能公式的这个作用,可惜没能多举例题说明,为引起对万能公式的重视,本文特举3例     

季节性数据的横断面建模方法

本文提出了一种对季节性数据建立数学模型的新方法──横断面方法．其思想是，把一个季节性时间序列划分成为数相当于一个季节周期长度的若干个子序列，在这些子序列中已完全消除了季节性因素，然后对这些子序列分别建立形式各异的数学模型，最后再把这些子序列的数学模型综合起来就得到了对原始序列的数学模型．     

原函数与定积分的关系

<正> 牛顿—莱布尼兹公式把计算定积分的问题化成求原函数的问题,给极大的一类函数提供     

一种模糊优化的全局算法及在三维水平井轨道设计中应用

本基于一种新的全局优化算法(EM)，提出一种求解模糊优化问题的全局优化算法。针对三维水平井轨道设计问题，提出两个模糊模型。最后把算法及模型应用到实际问题中，数值结果表明算法及模型是有效的、正确的。     

构造模型解题七例

构造法是通过构造数学模型来完成解题的一种解题方法，对有些数学问题，倘若充分的挖掘题设与结论之间的内在联系，把问题与某个熟悉的数学概念，公式定理，图形联系起来，并恰当的构造数学模型，就可以得到富有新意的独特的解法，在解题中往往能取的事半功倍的效果．利用构造法解题不仅构思巧妙，形式优美，过程简捷，而且能够锻炼思维的灵活性与...     

Mean-variance models for portfolio selection with fuzzy random returns

This paper develops two novel types of mean-variance models for portfolio selection problems, in which the security returns are assumed to be characterized by fuzzy random variables with known possibility and probability distributions. In the proposed models, we take the expected return of a portfolio as the investment return and the variance of the expected return of a portfolio as the investment risk. We assume that the security returns are triangular fuzzy random variables. To solve the proposed portfolio problems, this paper first presents the variance formulas for triangular fuzzy random variables. Then this paper applies the variance formulas to the proposed models so that the original portfolio problems can be reduced to nonlinear programming ones. Due to the reduced programming problems include standard normal distribution in the objective functions, we cannot employ the conventional solution methods to solve them. To overcome this difficulty, this paper employs genetic algorithm (GA) to solve them, and verify the obtained optimal solutions via Kuhn-Tucker (K-T) conditions. Finally, two numerical examples are presented to demonstrate the effectiveness of the proposed models and methods.     

Solving a full fuzzy linear programming using lexicography method and fuzzy approximate solution

This paper discusses full fuzzy linear programming (FFLP) problems of which all parameters and variable are triangular fuzzy numbers. We use the concept of the symmetric triangular fuzzy number and introduce an approach to defuzzify a general fuzzy quantity. For such a problem, first, the fuzzy triangular number is approximated to its nearest symmetric triangular number, with the assumption that all decision variables are symmetric triangular. An optimal solution to the above-mentioned problem is a symmetric fuzzy solution. Every FLP models turned into two crisp complex linear problems; first a problem is designed in which the center objective value will be calculated and since the center of a fuzzy number is preferred to (its) margin. With a special ranking on fuzzy numbers, the FFLP transform to multi objective linear programming (MOLP) where all variables and parameters are crisp.     

一类奇异型折扣费用模型之推广

设((?),(?),P)为一概率空间,(?)_t,t≥0为(?)中的上升(?)-域,W_t,t≥0为(?)_t,适应的标准 Wiener 过程,且对(?)0≤s≤t≤∞,W_t—W_s 与(?)_s 独立.以(?)表(?)_t 适应左连续0初值有限变差过程全体.对(?)ξ={ξ_t,t≥0}∈(?)有正规分解ξ_t=ξ_t~ —ξ_t~-,(?)_t(?)ξ_t~ ξ_t~-表ξ_t的全变差,当然ξ~ 及ξ_-皆(?)中单调非降过程.有关类型的折扣费用问题曾被不少人研究过,例如 Bene(?)等人的文章.后来这些     

Capacity allocation for demand of different customer-product-combinations with cancellations, no-shows, and overbooking when there is a sequential delivery of service

We consider a problem where different classes of customers can book different types of services in advance and the service company has to respond immediately to the booking request confirming or rejecting it. Due to the possibility of cancellations before the day of service, or no-shows at the day of service, overbooking the given capacity is a viable decision. The objective of the service company is to maximize profit made of class-type specific revenues, refunds for cancellations or no-shows as well as the cost of overtime. For the calculation of the latter, information of the underlying appointment schedule is required. Throughout the paper we will relate the problem to capacity allocation in radiology services. Drawing upon ideas from revenue management, overbooking, and appointment scheduling we model the problem as a Markov decision process in discrete time which due to proper aggregation can be optimally solved with an iterative stochastic dynamic programming approach. In an experimental study we successfully apply the approach to a real world problem with data from the radiology department of a hospital. Furthermore, we compare the optimal policy to four heuristic policies, of whom one is currently in use. We can show that the optimal policy significantly improves the currently used policy and that a nested booking limit type policy closely approximates the optimal policy and is thus recommended for use in practice.     

Portfolio adjusting optimization under credibility measures

This paper discusses portfolio adjusting problems for an existing portfolio. The returns of risky assets are regarded as fuzzy variables and a class of credibilistic mean-variance adjusting models with transaction costs are proposed on the basis of credibility theory. Under the assumption that the returns of risky assets are triangular fuzzy variables, the optimization models are converted into crisp forms. Furthermore, we employ the sequential quadratic programming method to work out the optimal strategy. Numerical examples illustrate the effectiveness of the proposed models and the influence of the transaction costs in portfolio selection.     

三角犹豫模糊Heronian平均算子及其在多属性决策中的应用

针对属性间含有关联信息的三角犹豫模糊多属性决策问题,提出一种基于三角犹豫模糊Heronian平均算子的决策方法。首先,考虑已有Heronian平均算子仅适用输入变量为两参数的情形,进一步定义三参数加权Heronian平均(TPWHM)和三参数加权几何Heronian平均(TPWGHM)算子,证明所提算子具有还原性、幂等性、单调性和有界性等性质,并研究它们的几种特例。其次,将TPWHM和TPWGHM算子推广至三角犹豫模糊决策环境下,提出三角犹豫模糊三参数加权Heronian平均(HTFTPWHM)和三角犹豫模糊三参数加权几何Heronian平均(HTFTPWGHM)算子,并证明算子的优良性质。在此基础上,提出基于两种算子的决策分析方法,并用来解决三角犹豫模糊决策问题。最后,通过算例验证所提方法的可行性和合理性。     

基于三角模糊数序列的灰色预测模型

以GM(1,1)模型为代表的灰色预测模型是以精确数序列为基础,难以满足实际需要.为了使灰色模型适应于模糊数序列,具体给出了一种基于三角模糊数序列的建模方法,这种方法也可以实现对二元区间模糊数和梯形模糊数序列的建模.首先由三角模糊数序列得出三个含有等量信息的精确数序列:重心序列、隶属函数的覆盖面积序列和中界点序列,对这三个序列分别建模后,再导出原始三角模糊数序列的三个界点的预测模型.这种建模方法既保持了模糊数的整体性又提高了建模序列的光滑度,提高了预测精度.最后进行了多组随机三角模糊数序列的数据模拟,验证了模型的有效性.     

模消去的Morita Contexts

证明了置换环上n-稳定秩条件关于Morita Context是遗传的;进一步把该结果推广到了强可分环,从而提供了新的具有模消去的置换环。     

非负权重最优组合预测方法的基本理论研究

本文从三个方面研究了非负权重最优组合预测方法的基本理论，给出了一种解决三阶非负权重最优组合预测问题的简捷方法。