A systematic approach to heterogeneous multiattribute group decision making

Heterogeneous multiattribute group decision making (MAGDM) problems which involve multi-granularity linguistic labels, fuzzy numbers, interval numbers and real numbers are very complex and important in practical applications of decision making theory. Hitherto, there exists no general theoretical inducement for solving such problems. The purpose of this paper is to develop a systematic methodology for solving the heterogeneous MAGDM problems by introducing the multiattribute ranking index based on the particular measure of closeness to the positive ideal solution (PIS) and using the weighted Minkowski distance to measure differences between each alternative and the PIS as well as the negative ideal solution (NIS). The proposed methodology is shown to have some advantages over the fuzzy TOPSIS. Validity and applicability of the methodology proposed in this paper is illustrated with a real example of the missile weapon system selection problem.     

A systematic approach to heterogeneous multiattribute group decision making

Heterogeneous multiattribute group decision making (MAGDM) problems which involve multi-granularity linguistic labels, fuzzy numbers, interval numbers and real numbers are very complex and important in practical applications of decision making theory. Hitherto, there exists no general theoretical inducement for solving such problems. The purpose of this paper is to develop a systematic methodology for solving the heterogeneous MAGDM problems by introducing the multiattribute ranking index based on the particular measure of closeness to the positive ideal solution (PIS) and using the weighted Minkowski distance to measure differences between each alternative and the PIS as well as the negative ideal solution (NIS). The proposed methodology is shown to have some advantages over the fuzzy TOPSIS. Validity and applicability of the methodology proposed in this paper is illustrated with a real example of the missile weapon system selection problem.     

Idea discovery: A scenario-based systematic approach for decision making in market innovation

A new trend of researches on knowledge discovery and chance discovery is to identify human insights through data synthesis rather than to discover facts through data analysis. In this paper, we propose a systematic approach named idea discovery which is committed to turning data into effective human insights. Idea discovery focuses on dynamic and sustainable process for high-quality ideas cultivation, construction, integration and evaluation through human–computer and human–human interaction. It mainly relies on latent information and its dynamic changes to drive ideas creation, integration and evaluation during sustainable creativity process. The process of idea discovery is in accordance with a dynamic model which contains two key components: (1) mining algorithms to turn data into scenario maps for eliciting human insights; (2) scenario-based creativity support activities towards actionable ideas generation. An intelligence system called Galaxy integrated with IdeaGraph algorithm has been developed to support the dynamic process of idea discovery. A case study in an automobile company has validated the effectiveness of proposed method and system.     

A hybrid decision making approach to prevent chatter vibrations

In this paper, the optimum cutting conditions without chatter vibrations have been determined during turning operations. Chatter vibrations are detrimental and cause poor surface properties. In this study, chatter vibration prevention has been discussed in a different way using a multi-criteria decision making approach. Regression-multi-criteria decision making hybrid models have been developed and applied to the problem of chatter vibrations. First, regression models have been used to determine the criteria weights for TOPSIS (technique for order preference by similarity to ideal solution) model. Then, TOPSIS models have been developed. Three different hybrid models have been studied. The results of these three models are the same. It has been seen from the results that the number of revolutions and the workpiece hardness are the most effective parameters. The models are developed to help operators in different manufacturing environments.     

A systematic decision making approach for product conceptual design based on fuzzy morphological matrix

Conceptual design plays an important role in development of new products and redesign of existing products. Morphological matrix is a popular tool for conceptual design. Although the morphological-matrix based conceptual design approaches are effective for generation of conceptual schemes, quantitative evaluation to each of the function solution principle is seldom considered, thus leading to the difficulty to identify the optimal conceptual design by combining these function solution principles. In addition, the uncertainties due to the subjective evaluations from engineers and customers in early design stage are not considered in these morphological-matrix based conceptual design approaches. To solve these problems, a systematic decision making approach is developed in this research for product conceptual design based on fuzzy morphological matrix to quantitatively evaluate function solution principles using knowledge and preferences of engineers and customers with subjective uncertainties. In this research, the morphological matrix is quantified by associating the properties of function solution principles with the information of customer preferences and product failures. Customer preferences for different function solution principles are obtained from multiple customers using fuzzy pairwise comparison (FPC). The fuzzy customer preference degree of each solution principle is then calculated by fuzzy logarithmic least square method (FLLSM). In addition, the product failure data are used to improve product reliability through fuzzy failure mode effects analysis (FMEA). Unlike the traditional FMEA, the causality relationships among failure modes of solution principles are analyzed to use failure information more effectively through constructing a directed failure causality relationship diagram (DFCRD). A fuzzy multi-objective optimization model is also developed to solve the conceptual design problem. The effectiveness of this new approach is demonstrated using a real-world application for conceptual design of a horizontal directional drilling machine (HDDM).     

A knowledge‐based approach to adversarial decision making

Our focus here is to provide a methodology that can be used by a participant in an adversarial decision‐making environment to help choose their action. Central to our approach is the use of knowledge and perceptions about one's adversary to obtain an uncertainty profile indicating which action the adversary will take. Once having this uncertainty profile, the problem of deciding which action to take becomes a problem of decision making under uncertainty. Here, we make considerable use of the Dempster‐‐Shafer belief structure as a way of formalizing the uncertainties. © 2008 Wiley Periodicals, Inc.     

一类基于优势关系的不完全信息多属性决策方法

针对属性权重和属性值信息均不完全,且含有非线性形式的多属性决策问题,提出一种基于优势关系实现方案择优与排序的决策方法.首先定义方案优势、弱优势和潜在优关系,构建等价的非线性规划模型,确定优势和潜在优方案;然后揭示、论证了非劣集与潜在优集的关系,提出了方案优势度指标,并据此给出了方案择优与排序的实现步骤;最后,提出采用变量替换法求解非线性决策模型.实例计算结果表明,所提出的方法是可行且有效的.     

一种新的灰色多属性决策方法

针对模糊群体多属性决策问题,提出一种新的灰色多属性决策方法.该方法依据一般的灰色关联分析方法的基本思路,将灰色关联度和欧氏距离有机结合,构造出一种平均相似度对方案进行评价.平均相似度同时反映了方案与正负理想方案之间的位置和数据曲线的相似性差异,其物理意义更加明确.最后通过算例表明了所提出方法的可行性和有效性.     

Pythagorean fuzzy TODIM approach to multi-criteria decision making

Recently, the TODIM (an acronym in Portuguese for Interactive Multi-criteria Decision Making) approach, which can characterize the decision makers’ psychological behaviours under risk, has been introduced to handle multi-criteria decision making (MCDM) problems. Moreover, Pythagorean fuzzy set is an effective tool for depicting uncertainty of the MCDM problems. In this paper, based on the prospect theory, we first extend the TODIM approach to solve the MCDM problems with Pythagorean fuzzy information. Then, we conduct simulation tests to analyze how the risk attitudes of the decision makers exert the influence on the results of MCDM under uncertainty. Finally, a case study on selecting the governor of Asian Infrastructure Investment Bank is made to show the applicability of the proposed approach.     

A novel approach to multi-attribute decision making based on intuitionistic fuzzy sets

In this paper we present a new approach to solve multi-attribute decision making problems in intuitionistic fuzzy environment. This approach is based on a new ranking method of intuitionistic fuzzy sets, in which the evaluated values (in the form of intervals) of the same alternative with different attributes are considered as one unified entity. According to people’s intuition, the ranking method proposed in this paper is mainly grounded on a revised score function and a revised accuracy function of intuitionistic fuzzy sets. Different from the traditional methods, in this new approach, the degree of membership, the degree of nonmembership and the degree of hesitation are considered with various importance in reflecting the true image of the respective alternative. Furthermore, an optimization model is established to estimate the relative degree of importance of each quantity. Finally, two practical examples are provided to illustrate our approach.     

An approach to fuzzy multiattribute decision making under uncertainty

It seems that there is little investigation on fuzzy multiattribute decision making (FMADM) problems under uncertainty, which are of important to scientific researches and real life applications. FMADM problems under uncertainty are investigated in this paper. Novel mathematical programming models are constructed for FMADM problems under uncertainty, and corresponding solving methods are proposed. The approach proposed in this paper may reflect both subjective judgment and objective information. Moreover, pairwise chain comparison methods for determination of relative membership degrees and weights are also proposed. Feasibility and effectiveness of the models and approach proposed in this paper are illustrated with a numerical example.     

A hybrid data envelopment analysis and multi-attribute decision making approach to sustainability assessment

The concept of sustainability consists of three main dimensions: environmental, techno-economic, and social. Measuring the sustainability status of a system or technology is a significant challenge, especially when it needs to consider a large number of attributes in each dimension of sustainability. In this study, we first propose a hybrid approach, involving data envelopment analysis (DEA) and a multi-attribute decision making (MADM) methodologies, for computing an index for each dimension of sustainability, and then we define the overall sustainability index as the mean of the three measured indexes. Towards this end, we define new concepts of efficiency and cross-efficiency of order (p, q) where p and q are the number of inputs and outputs, respectively. For a given (p, q) , we address the problem of finding efficiency of order (p, q) by developing a novel DEA-based selecting method. Finally, we define the sustainability index as a weighted sum of all possible cross-efficiencies of order (p, q) . Form a computational viewpoint, the proposed selecting model significantly decreases the computational burden in comparison with the successive solving of traditional DEA models. A case study of the electricity-generation technologies in the United Kingdom is taken as a real-world example to illustrate the potential application of our method.     

GACRM: A dynamic multi-Attribute decision making approach to large-Scale Web service composition

The problem of QoS-aware Web service composition (QWSC), i.e., how to select from a pool of candidate services to construct a composite service with the best overall QoS performance, is an NP-hard problem. To address a large-scale QWSC problem, a novel method is proposed based on information theory, multi-attribute decision making (MADM) and genetic algorithm. To capture complex judgments, the QWSC problem is formulated into a MADM representation which aims to find acceptable solutions assessed by multiple QoS attributes with varying distributions. To solve the MADM problem for QWSC, each QoS attribute is weighted in both a priori, subjective perspective and a posteriori, information-based perspective based on the discriminative capability of QoS attributes for a dynamic pool of candidate services. Furthermore, to solve the large-scale QWSC problem that conventional MADM methods cannot navigate, we develop a GACRM algorithm by integrating genetic algorithm (GA) with Compromise Ratio Method (CRM). Experiments demonstrate that GACRM obtains nearly the same solution ranking by the CRM but scales much better in terms of computation time for large-scale QWSC problems.     

A view of group decision making process and bivoting approach

Many characteristics of Group Decision Making (GDM) are different from those of individual decision. The literature dealing with the stages of GDM is rather scant. This paper presents a view about the stages of group decision processes, characterizing GDM as a dynamic process. We discuss particularly the aggregation stage of preferences and reports a bivoting approach' used in practising group decision support systems (GDSS). Finally, a concrete example is given to illustrate each stage of group decision process and tile 'bivoting approach' in consensus reaching stage.     

A mathematical programming approach to multi-attribute decision making with interval-valued intuitionistic fuzzy assessment information

This article proposes an approach to handle multi-attribute decision making (MADM) problems under the interval-valued intuitionistic fuzzy environment, in which both assessments of alternatives on attributes (hereafter, referred to as attribute values) and attribute weights are provided as interval-valued intuitionistic fuzzy numbers (IVIFNs). The notion of relative closeness is extended to interval values to accommodate IVIFN decision data, and fractional programming models are developed based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to determine a relative closeness interval where attribute weights are independently determined for each alternative. By employing a series of optimization models, a quadratic program is established for obtaining a unified attribute weight vector, whereby the individual IVIFN attribute values are aggregated into relative closeness intervals to the ideal solution for final ranking. An illustrative supplier selection problem is employed to demonstrate how to apply the proposed procedure.     

A parallel algorithm for real-time decision making: A rough set approach

We consider decision tables with the values of conditional attributes (conditions) measured by sensors. These sensors produce outputs after an unknown but finite number of time units. We construct an algorithm for computing a highly parallel program represented by a Petri net from a given decision table. The constructed net allows to identify objects in decision tables to an extent which makes appropriate decisions possible. The outputs from sensors are propagated through the net with maximal speed. This is done by an appropriate implementation of all rules true in a given decision table. Our approach is based on rough set theory (Pawlak, 1991). It also seems to have some significance for theoretical foundations of real-time systems.     

A new method selection approach for fuzzy group multicriteria decision making

Fuzzy multicriteria decision making (MCDM) has been widely used in ranking a finite number of decision alternatives characterized by fuzzy assessments with respect to multiple criteria. In group decision settings, different fuzzy group MCDM methods often produce inconsistent ranking outcomes for the same problem. To address the ranking inconsistency problem in fuzzy group MCDM, this paper develops a new method selection approach for selecting a fuzzy group MCDM method that produces the most preferred group ranking outcome for a given problem. Based on two group averaging methods, three aggregation procedures and three defuzzification methods, 18 fuzzy group MCDM methods are developed as an illustration to solve the general fuzzy MCDM problem that requires cardinal ranking of the decision alternatives. The approach selects the group ranking outcome of a fuzzy MCDM method which has the highest consistency degree with its corresponding ranking outcomes of individual decision makers. An empirical study on the green bus fuel technology selection problem is used to illustrate how the approach works. The approach is applicable to large-scale group multicriteria decision problems where inconsistent ranking outcomes often exist between different fuzzy MCDM methods.     

战场目标打击顺序的多属性决策方法

提出了一种战场目标打击顺序的多属性决策方法,该方法把主观和客观信息集成起来,通过一个数学规划模型把获得的战场目标客观信息与决策者给出的主观权重偏好信息有机地集成,使属性的权重可在决策者主观基础上根据战场态势动态调整,利用TOPSIS方法排定目标的打击顺序,为战场目标的打击顺序问题提出了一种新的解决方法.     

Using a multi-criteria decision making approach to evaluate mobile phone alternatives

The arrival of the mobile phone and its rapid and widespread growth may well be seen as one of the most significant developments in the fields of communication and information technology over the past two decades. The aim of this study is to propose a multi-criteria decision making (MCDM) approach to evaluate the mobile phone options in respect to the users' preferences order. Firstly, the most desirable features influencing the choice of a mobile phone are identified. This is realized through a survey conducted among the target group, the experiences of the telecommunication sector experts and the studies in the literature. Two MCDM methods are then used in the evaluation procedure. More precisely, Analytic Hierarchy Process (AHP) is applied to determine the relative weights of evaluation criteria and the extension of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied to rank the mobile phone alternatives. A case study illustrates the effectiveness of the proposed approach.