多属性群决策的直觉梯形模糊数法

采用直觉梯形模糊数刻画专家的评价信息,提出一种新的多属性群决策方法.定义了直觉梯形模糊数的期望值、预期得分、有序加权集成算子和混合集成算子;建立了基于直觉梯形模糊数的多属性群决策模型;通过混合集成算子得到方案的群体综合评估值,根据期望值和预期得分给出群决策结果.实例分析验证了所提出方法的有效性.     

基于改进遗传算法的一类多属性群决策方法

通过定义个体决策结果和群体决策结果的加权距离来反映决策结果的一致性,并通过定义对打分矩阵的调整程度来反映对决策者最初决策偏好的调整.在保留各决策者最初决策偏好的基础上,对原始专家打分矩阵进行调整,得到新的一致性较好的群决策结果.采用遗传算法对问题求解,以打分矩阵为基础设计了一种染色体编码格式,并对标准遗传算法进行了改进,提出了基于规则的遗传算法.最后,通过实例计算和结果的可靠度分析表明了该方法的有效性和合理性.     

Interval programming method for hesitant fuzzy multi-attribute group decision making with incomplete preference over alternatives

The aim of this study is to employ the main structure of LINMAP (LINear programming technique for Multidimensional Analysis of Preference) to propose an interval programming method for solving multi-attribute group decision making (MAGDM) problems in which the ratings of alternatives are taken as hesitant fuzzy elements (HFEs) and all pair-wise comparison judgments over alternatives are represented by interval numbers. The contribution of this study is fivefold: (1) we define the new consistency and inconsistency indices; (2) we construct an interval programming model to determine the hesitant fuzzy positive ideal solution and the optimal weights of attributes, and at the same time present a decision algorithm; (3) we discuss several special cases of the proposed model in detail; (4) we show that compared with intuitionistic fuzzy LINMAP method (Li et al., 2010), the proposed approach reveals more useful information including the interval preference information, and does not need to transform HFEs into intuitionistic fuzzy numbers but directly deals with MAGDM problems and thus obtains better final decision results; and (5) we demonstrate the applicability and implementation process of the proposed approach by using an energy project selection example.     

基于二次规划的直觉模糊数的多属性决策方法

针对属性权重完全未知且属性值为直觉模糊数的多属性决策问题,提出了一种新的决策方法。首先引入了直觉模糊数的一些运算法则、得分函数和精确函数等概念。然后构建了一个二次规划模型,通过求解该模型获得属性的权重。接着利用直觉模糊加权平均(IFWA)算子对属性值进行集结,得到方案的综合属性值。最后利用得分函数和精确函数对方案进行排序并择优。给出的算例说明了该方法的实用性和可行性。     

An agent architecture for multi-attribute negotiation using incomplete preference information

A component-based generic agent architecture for multi-attribute (integrative) negotiation is introduced and its application is described in a prototype system for negotiation about cars, developed in cooperation with, among others, Dutch Telecom KPN. The approach can be characterized as cooperative one-to-one multi-criteria negotiation in which the privacy of both parties is protected as much as desired. We model a mechanism in which agents are able to use any amount of incomplete preference information revealed by the negotiation partner in order to improve the efficiency of the reached agreements. Moreover, we show that the outcome of such a negotiation can be further improved by incorporating a “guessing” heuristic, by which an agent uses the history of the opponent’s bids to predict his preferences. Experimental evaluation shows that the combination of these two strategies leads to agreement points close to or on the Pareto-efficient frontier. The main original contribution of this paper is that it shows that it is possible for parties in a cooperative negotiation to reveal only a limited amount of preference information to each other, but still obtain significant joint gains in the outcome.     

Use of multi-attribute decision analysis for designing operations system framework in telecommunications management network

This paper is concerned with the design of an Operations System (OS) framework for implementing a proper telecommunications network in Korea Telecom. Since several types of OS frameworks are under consideration, the telecommunication network manager should now choose the best alternative for use later in establishing the infrastructure of operations systems. The decision making is done in this paper by means of a Multi-Attribute Decision-Making (MADM) analysis. A point to be noted in the present case is that the decision relevant information such as attribute weights and values of alternatives are not known exactly. Rather, these are to be taken in the form of rankings and/or bounds. To deal with such incomplete information, we employ a mathematical programming model-based MADM approach to the choice of an optimal OS framework design. This approach enables us to check dominance of alternatives and to obtain a set of non-dominated alternatives from evaluating five alternatives in reference to Telecommunications Management Network (TMN) standards.

Scope and purpose

Telecommunications Management Network (TMN) can be stated as a globalized and unified skeleton to meet the advanced operational environments of telecommunications networks and to handle heterogeneous and complex network elements. Although there are various subjects that should be addressed to accomplish TMN, we confine our attention to dealing with one important subject, design of an Operations System (OS) framework. This is necessary to manage telecommunications resources including networks in effective manner and for use as guidance in developing individual operations systems and in constructing a network management center.Several types of OS frameworks have been suggested by TMN standards. It is hence needed to evaluate each of these OS frameworks and then to choose an appropriate one in Korean TMN situation. Since this evaluation involves multiple criteria (or attributes), it is realized in this paper by a Multi-Attribute Decision-Making (MADM) analysis approach. The decision relevant information such as trade-off weights and individual criterion values are elicited from expert opinions which, however, is rather incomplete than exact numerical values. The decision making process with the incompletely identified information is presented in this paper.     

Divergence-based cross entropy and uncertainty measures of Atanassov’s intuitionistic fuzzy sets with their application in decision making

The uncertainty measure of Atanassov’s intuitionistic fuzzy sets (AIFSs) is important for information discrimination under intuitionistic fuzzy environment. Although many entropy measures and knowledge measures haven been proposed to depict uncertainty of AIFSs, how to measure the uncertainty of AIFSs is still an open topic. The relation between uncertainty and other measures like entropy measures, fuzziness and intuitionism is not clear. This paper introduces uncertainty measures by using new defined divergence-based cross entropy measure of AIFSs. Axiomatic properties of the developed uncertainty measure are analysis, together with the monotony property of uncertainty degree with respect to fuzziness and intuitionism. To adjust the contribution of fuzzy entropy and intuitionistic entropy on the total uncertainty, the proposed cross entropy and uncertainty measures are parameterized. Numerical examples indicate the effectiveness and agility of the biparametric uncertainty measure in quantifying uncertainty degree. Then we apply the cross entropy and uncertainty measures into an optimal model to determine attribute weights in multi-attribute group decision making (MAGDM) problems. A new method for intuitionistic fuzzy MAGDM problems is proposed to show the efficiency of proposed measures in applications. It is demonstrated by application examples that the proposed measures can get reasonable results coinciding with other existing methods.     

一种基于非功能属性决策的可信Web服务发现模型

Web服务注册中心为服务请求者寻找Web服务带来方便,但由于其缺少对服务非功能信息的支持,无法很好满足用户需求,最终导致服务发现可信程度不高.首先对Web服务质量、服务信誉等非功能属性进行分析,通过服务行为观测机制获取较客观的属性指标数据,利用多属性决策方法,提出一种可信的Web服务发现模型.模型能帮助服务请求者发现最优的、可信的服务.最后通过一个应用实例验证了模型的有效性.     

Agent based intelligent search framework for product information using ontology mapping

The Semantic Web and Web services provide many opportunities in various applications such as product search and comparison in electronic commerce. We implemented an intelligent meta-search and recommendation system for products through consideration of multiple attributes by using ontology mapping and Web services. Under the assumption that each shopping site offers product ontology and product search service with Web services, we proposed a meta-search framework to configure a customer’s search intent, make and dispatch proper queries to each shopping site, evaluate search results from shopping sites, and show the customer the relevant product list with associated rankings. Ontology mapping is used for generating proper queries for shopping sites that have different product categories. We also implemented our framework and performed empirical evaluation of our approach with two leading shopping sites in the world.     

多属性逆向拍卖中供应商的投标策略

多属性采购拍卖在企业采购中具有重要意义。在已知买方效用函数的前提下,传统多属性采购拍卖 主要从买家角度出发,致力于拍卖机制和赢者决定问题,而供应商的决策模型少有研究。在采购商的效用函数未知 的前提下,基于DEA理论,利用以往赢家的信息建立了供应商投标的数学模型,并通过数值例子阐述了模型了应用 价值。所得结果既有助于供应商正确推断卖方属性偏好权重值,确定投标策略,增加胜标机会,又有助于提高供应 商的能力,促进供应商之间的竞争,增加采购商的效用。