基于区间直觉模糊不确定语言的中小企业电子商务网站建设决策方法研究

阐述中小企业在整个国民经济中的重要地位,指出电子商务对于中小企业具有天然的适应性和可行的推广性.揭示研究对象中蕴含着广泛的模糊性,应用区间直觉模糊不确定语言的必要性.介绍区间直觉模糊不确定语言的基本概念、基本运算、算术平均和加权平均、距离、期望函数、精度函数、期望函数值、精度函数值以及对象比较方法等内容.提出区间直觉模糊不确定语言决策步骤:设定方案集、指标集、专家集,确定评判矩阵,确定指标权重,计算加权平均,计算期望函数、精度函数,期望函数值、精度函数值,进行排序.以盛东商贸有限公司电子商务网站设计方案测评为例,碍出方案3优于方案2优于方案5优于方案1优于方案4的结论.     

A parametric GP model dealing with incomplete information for group decision-making

We consider a group decision-making problem where preferences given by the experts are articulated into the form of pairwise comparison matrices. In many cases, experts are not able to efficiently provide their preferences on some aspects of the problem because of a large number of alternatives, limited expertise related to some problem domain, unavailable data, etc., resulting in incomplete pairwise comparison matrices. Our goal is to develop a computational method to retrieve a group priority vector of the considered alternatives dealing with incomplete information. For that purpose, we have established an optimization problem in which a similarity function and a parametric compromise function are defined. Associated to this problem, a logarithmic goal programming formulation is considered to provide an effective procedure to compute the solution. Moreover, the parameters involved in the method have a clear meaning in the context of group problems.     

一种新型风险型多指标决策方法研究

传统的风险型多指标决策模型没有考虑决策者对风险的态度,而决策者对风险的态度会影响决策的结果,针对这一问题文章在累积前景理论与灰色关联方法的基础上,提出一种考虑决策者风险偏好的风险型多指标决策的方法.该方法首先利用极差化法对风险决策矩阵进行规范化处理,并在此基础上构造出最优与最劣方案;然后利用累积前景理论与灰色关联方法构建前景值函数,并给出利用灰色关联思想确定指标权重的方法与步骤;最终求出各个方案的综合前景值并进行排序选优.通过某电信运营商对管道资源建设方案选择的实例分析说明了方法的可行性与有效性.     

基于SMAA和公共权重的决策单元效率评价与排序

在数据包络分析(DEA)中,公共权重模型是决策单元效率评价与排序的常用方法之一。与传统DEA模型相比,公共权重模型用一组公共的投入产出权重评价所有决策单元,评价结果往往更具有区分度且更为客观。本文考虑决策单元对排序位置的满意程度,提出了基于最大化最小满意度和最大化平均满意度两类新的公共权重模型。首先,基于随机多准则可接受度分析(SMAA)方法,计算出每个决策单元处于各个排名位置的可接受度;然后,通过逆权重空间分析,分别求得使最小满意度和平均满意度最大化的一组公共权重;最后,利用所求的公共权重,计算各决策单元的效率值及相应的排序。算例分析验证了本文提出的基于SMAA的公共权重模型用于决策单元效率评价与排序的可行性。     

On the cardinality of the Pareto set in bicriteria shortest path problems

Computing shortest paths with two or more conflicting optimization criteria is a fundamental problem in transportation and logistics. We study the problem of finding all Pareto-optimal solutions for the multi-criteria single-source shortest-path problem with nonnegative edge lengths. The standard approaches are generalizations of label-setting (Dijkstra) and label-correcting algorithms, in which the distance labels are multi-dimensional and more than one distance label is maintained for each node. The crucial parameter for the run time and space consumption is the total number of Pareto optima. In general, this value can be exponentially large in the input size. However, in various practical applications one can observe that the input data has certain characteristics, which may lead to a much smaller number—small enough to make the problem efficiently tractable from a practical viewpoint. For typical characteristics which occur in various applications we study in this paper whether we can bound the size of the Pareto set to a polynomial size or not. These characteristics are also evaluated (1) on a concrete application scenario (computing the set of best train connections in view of travel time, fare, and number of train changes) and (2) on a simplified randomized model. It will turn out that the number of Pareto optima on each visited node is restricted by a small constant in our concrete application, and that the size of the Pareto set is much smaller than our worst case bounds in the randomized model. A preliminary short version of this paper appeared in the Proceedings of the 5th Workshop on Algorithm Engineering (WAE 2001), LNCS 2141, Springer Verlag, pp. 185–197 (2001) under the title “Pareto shortest paths is often feasible in practice.”     

k-intolerant capacities and Choquet integrals

We define an aggregation function to be (at most) k-intolerant if it is bounded from above by its kth lowest input value. Applying this definition to the discrete Choquet integral and its underlying capacity, we introduce the concept of k-intolerant capacities which, when varying k from 1 to n, cover all the possible capacities on n objects. Just as the concepts of k-additive capacities and p-symmetric capacities have been previously introduced essentially to overcome the problem of computational complexity of capacities, k-intolerant capacities are proposed here for the same purpose but also for dealing with intolerant or tolerant behaviors of aggregation. We also introduce axiomatically indices to appraise the extent to which a given capacity is k-intolerant and we apply them on a particular recruiting problem.     

一种基于Spearman秩相关系数与熵的多属性决策方法

本以方案间单个指标的关联系数为基础，引入相关度概念，对以关联系数平均值作为测度的评价方法进行了改进，提出了以方案相关度为测度指标的新的决策方法。     

线性规划在最优火力分配辅助决策中的应用

采用层次分析法和线性规划法对坦克连冲击时目标价值和火力分配问题进行了分析.在理论分析的基础上,用C++Builder开发火力分配辅助决策软件,该软件以报告文件的形式显示目标价值结果,以报告文件或图形的方式显示火力分配结果.     

一种基于合作与满意的群决策方法

从信息熵和相对熵的概念出发 ,提出了“不合作度”和“不满意度”的概念 ,通过论证指出了理想合作群“不合作度”和“不满意度”均为零的特点 .针对此特点 ,建立了基于“不合作度”和“不满意度”最小的优化模型 ,并针对模型 ,对遗传算法进行改进 ,使之适合于求解模型 .最后通过算例表明了此群决策方法的有效性和实用性 .