基于可能度排序法的区间信息指派方法

针对具有区间数信息的多目标指派问题,利用区间数可能度排序方法,给出了一种新的指派方法.该方法充分利用实际所给的区间信息进行求解,克服了以往这类指派问题最后由多目标问题转换为单目标问题时权数确定主观性大的缺陷.最后给出了该方法的一个算例.     

基于累积前景理论的具有不完全序值信息的双边匹配决策方法

针对带有主体期望值的具有不完全序值信息的双边匹配问题,提出了一种基于累积前景理论的决策方法。在文中,给出了该双边匹配问题的描述;将主体给出的期望值视为参照点,构建了相对参照点的益损矩阵;依据累积前景理论和规范化公式,将益损矩阵转化为规范化前景矩阵;在此基础上,构建了求解该双边匹配问题的多目标优化模型,使用线性加权法将多目标优化模型转化为单目标优化模型,通过求解该单目标优化模型获得匹配结果;最后,通过一个实例说明了所提方法的可行性和有效性。     

多目标指派问题在潜艇兵力配置中的应用

运用模糊数学的思想，首先将各目标下的属性值矩阵转化为模糊关系矩阵，再将模糊关系合成矩阵与解决传统指派问题的匈牙利法相结合，提出一种求解多目标指派问题的综合方法：模糊匈牙利法，并结合优化潜艇兵力配置问题进行了应用分析。     

基于目标规划和相对优势度的区间数互反判断矩阵排序法

针对决策信息以区间数互反判断矩阵形式给出的多目标决策问题.首先,给出了区间数一致性互反判断矩阵、相对优势度等概念.其次,建立一个目标规划模型,通过求解该模型得到区间数互反判断矩阵的权重向量,并利用各方案的相对优势度和进行方案的排序.提出了一种新的区间数互反判断矩阵排序方法,该方法具有操作简便和易于上机实现的特点.最后,通过实例说明方法的可行性和有效性.     

供给总量限定需求区间约束型运输问题——时限费用优化模型与算法

本文目的是为建立与运输问题有关的决策支持系统提供方便.本文建立了供给总量限定需求区间约束型运输问题的对时限与费用两个目标进行优化的多目标规划模型,给出了求解模型的算法,并举例说明了算法的应用.该算法能求得问题的最优解,并具有易于编程实现、收敛性好等优点.数值实验表明该算法有较高的计算效率,可用于求解某些类型的指派问题.     

网络团购环境下基于电子中介的商品交易优化模型

在网络团购环境下,如何考虑顾客、商家和电子中介三方主体的利益并实现商品交易最优化,这是一个值得关注的研究问题。本文针对基于电子中介的网络团购商品交易问题,依据商家与电子中介事先商定的团购商品的交易数量区间、交易数量折扣以及顾客和商家分别提交的商品的报价和保留价,在考虑顾客、商家和电子中介三方利益最大化的前提下,构建了多目标商品交易优化模型;进一步地,将多目标优化模型转化为单目标优化模型,并给出了求解优化模型的遗传算法。最后,通过一个算例说明了本文构建的模型及其求解算法的可行性和有效性。     

基于最小偏差和优势度的区间数互补判断矩阵排序法

针对决策信息以区间数互补判断矩阵形式给出的多目标决策问题。首先,给出相对优势度的概念和区间数加性一致性互补判断矩阵的判定定理。其次,建立一个目标规划模型,通过求解该模型得到区间数互补判断矩阵的权重向量,并利用各权重向量的总体相对优势度对方案进行排序,提出了基于最小偏差和优势度的区间数互补判断矩阵排序法。方法的核心是对数值型互补判断矩阵排序方法的拓展。最后,通过实例说明方法的可行性和有效性。     

有资格限制的指派问题的求解方法

在实际的指派工作中，常会遇到某个人有没有资格去承担某项工作的问题，因此，本建立了有资格限制的指派问题的数学模型。在此数学模型中，将效益矩阵转化为判定矩阵，由此给出了判定此种指派问题是否有解的方法；在有解的情况下，进一步将效益矩阵转化为求解矩阵，从而将有资格限制的指派问题化为传统的指派问题来求解。最后给出了一个数值例子来说明这样的处理方法是有效的。     

非平衡指派模型及其在航空机务维修中的应用

非平衡指派问题是最优平衡指派问题的推广与深化,在航空机务维修工作中,维修任务的合理配置对及时完成维修任务,保障训练作战计划非常重要.本文从装备完好率和人力资源的优化配置角度出发,按照不考虑维修任务等待时间和考虑维修任务等待时间两种情况分别建立了非平衡指派优化模型,并给出了这两种情况下效益矩阵的构造方法,进而将优化模型转化为最优平衡指派模型进行求解,从而为航空机务维修工作中维修人员的优化配置提供了一种科学、合理的决策方法.     

电子采购中具有语言评价信息的交易匹配问题研究

针对电子采购中具有语言评价信息的买方与卖方交易匹配问题,提出了一种决策分析方法.首先,给出了电子采购中基于电子中介的买方与卖方交易匹配的问题描述;然后在此基础上,将买方与卖方给出的具有语言评价信息的效率矩阵转化为二元语义形式,考虑以买方与卖方双方满意度最大为目标构建了多目标优化模型,根据二元语义的自身特点将模型进行转化,并最终转化为单目标线性规划模型进行求解来得到交易匹配结果;最后,通过电子采购中交易匹配的实例分析说明了本文给出方法的可行性和实用性.     

A group decision making approach based on aggregating interval data into interval-valued intuitionistic fuzzy information

Group decision making is one of the most important problems in decision making sciences. The aim of this article is to aggregate the interval data into the interval-valued intuitionistic fuzzy information for multiple attribute group decision making. In this model, the decision information is provided by decision maker, which is characterized by interval data. Based on the idea of mean and variance in statistics, we first define the concepts of satisfactory and dissatisfactory intervals of attribute vector against each alternative. Using these concepts, we develop an approach to aggregate the attribute vector into interval-valued intuitionistic fuzzy number under group decision making environment. A practical example is provided to illustrate the proposed method. To show the validity of the reported method, comparisons with other methods are also made.     

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The log-normal distribution is a common choice for modeling positively skewed data arising from many practical applications.This article introduces a new method of constructing confidence interval for a common mean shared by several log-normal populations through confidence distributions, which combines all information from independent sources. We develop a non-trivial weighting approach by taking account of the sample variances of related quantities to enhance efficiency. Combined confidence distributions are used to construct confidence intervals for the common mean and a simplified version of one existing method is also proposed. We conduct simulation studies to evaluate the performance of the proposed methods in comparison with existing methods. Our simulation results show that the weighting approach yields shorter interval length than the non-weighting approach. The newly proposed confidence intervals perform very well in terms of empirical coverage probability and average interval length. Finally, applications of the proposed methodology is illustrated through three real data examples.     

基于灰色关联度的区间信息指派问题研究

研究了损益矩阵为区间数的不确定型指派问题,给出了区间数关联度的计算公式,提出了一种基于区间数关联度的区间信息指派方法,最后通过实例验证了该方法的实用性和有效性.     

Research on AHP with interval-valued intuitionistic fuzzy sets and its application in multi-criteria decision making problems

This paper investigates an approach for multi-criterion decision making (MCDM) problems with interval-valued intuitionistic fuzzy preference relations (IVIFPRs). Based on the novel interval score function, some extended concepts associated with IVIFPRs are defined, including the score matrix, the approximate optimal transfer matrix and the possibility degree matrix. By using these new matrixes, a prioritization method for IVIFPRs is proposed. Then, we investigate an interval-valued intuitionistic fuzzy AHP method for multi-criteria decision making (MCDM) problems. In the end, a numerical example is provided to illustrate the application of the proposed approach.     

A step-by-step method with Laguerre functions for solving time-dependent problems

A step-by-step modification of the well-known approach proposed by Mikhaylenko and Konyukh to solving dynamic problems is proposed. The approach is based on the Laguerre transform with respect to time. In this modification the Laguerre transform is applied to a sequence of finite time intervals. The solution obtained at the end of a time interval is used as the initial data for solving the problem on the next time interval. The method is illustrated by examples for the harmonic oscillator problem and the 1D wave equation. Accuracy and stability of the method are analyzed. This approach allows obtaining a solution of high accuracy on large time intervals.     

An enhanced subinterval analysis method for uncertain structural problems

This paper proposes an enhanced subinterval analysis method to predict the bounds of structural response with interval parameters, which could deal with problems with relatively large uncertainties of the parameters. The intervals are first divided into several subintervals, and two expansion routes are then constructed based on the sensitivity analysis. Two subinterval sets are selected according to the expansion points on the routes, and the first order Taylor expansion method is then adopted to complete the subinterval analysis. Based on the selected subinterval sets, the upper and lower bounds of the structural response are further obtained by employing the interval union operation. An adaptive convergence approach is presented to determine the appropriate number of subintervals. Four numerical examples are investigated to demonstrate the validity of the proposed method.     

Solving the Generalized Machine Assignment Problem in Group Technology

Many existing solution methodologies for machine assignment problems in group technology do not consider factors such as part demand, operation sequence and cost of intercellular moves. We formulate a 0-1 quadratic programming model that takes into account these factors in machine assignment. Two approaches are proposed to solve this problem. The first is an A*-based approach that generates optimal solutions. The second is a heuristic approach developed to solve problems with large number of machines and/or parts. The heuristic approach is shown to be efficient in producing good solutions in a computational study.     

一种考虑决策者风险偏好的区间数多属性决策方法

针对属性值以区间数形式给出的多属性决策问题,提出了一种决策分析方法。在本文中,首先描述了属性值为区间数形式的多属性决策问题;然后通过引入决策者的风险偏好因子将区间数决策信息映射为实数值决策信息,并依据属性值与属性均值绝对偏差的大小确定了属性的权重,在此基础上依据所得权重给出了基于加权和法的方案排序方法,通过对风险偏好因子的不同取值还可进行方案排序的灵敏度分析。最后,通过一个算例说明了本文给出方法的可行性和有效性。