The Research of Multiple Attribute Group Decision-Making Method Based on Cloud-PROMETHEE

2014 ◽  
Vol 672-674 ◽  
pp. 2140-2145
Author(s):  
Ying Peng Zhang ◽  
Zhi Fang Gao ◽  
Ding Hong Peng
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Planning Process ◽  
Group Decision ◽  
Cloud Model ◽  
Decision Matrix ◽  
Multiple Attribute ◽  
New Energy ◽  
Promethee Method ◽  
Energy Products

For the problem of interval multiple attribute group decision-making, this paper studies the Cloud-PROMETHEE method. First, we can obtain the comprehensive weight. Second, we transform the interval decision matrix into cloud by cloud model because of randomness and fuzziness of date information. With the help of the PROMETHEE, we use overall priority index to determine the order of alternatives. Finally, an example concerns analysis, which is the risk analysis of planning process of new energy products, is given to show the feasibility and availability of the method.

scholarly journals Hybrid Multiattribute Group Decision Making Based on Intuitionistic Fuzzy Information and GRA Method

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Jian Guo
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Ideal Solution ◽  
Decision Matrix ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Intuitionistic Fuzzy Entropy ◽  
Fuzzy Group Decision Making

Hybrid multiple attribute group decision making involves ranking and selecting competing courses of action available using attributes to evaluate the alternatives. The decision makers assessment information can be expressed in the form of real number, interval-valued number, linguistic variable, and the intuitionistic fuzzy number. All these evaluation information can be transformed to the form of intuitionistic fuzzy numbers. A combined GRA with intuitionistic fuzzy group decision-making approach is proposed. Firstly, the hybrid decision matrix is standardized and then transformed into an intuitionistic fuzzy decision matrix. Then, intuitionistic fuzzy averaging operator is utilized to aggregate opinions of decision makers. Intuitionistic fuzzy entropy is utilized to obtain the entropy weights of the criteria, respectively. After intuitionistic fuzzy positive ideal solution and intuitionistic fuzzy negative ideal solution are calculated, the grey relative relational degree of alternatives is obtained and alternatives are ranked. In the end, a numerical example illustrates the validity and applicability of the proposed method.

scholarly journals RISKY MULTI-CRITERIA GROUP DECISION MAKING ON GREEN CAPACITY INVESTMENT PROJECTS BASED ON SUPPLY CHAIN

2017 ◽  
Vol 18 (3) ◽  
pp. 355-372 ◽  
Author(s):  
Yan SONG ◽  
Shuang YAO ◽  
Donghua YU ◽  
Yan SHEN
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Group Decision Making ◽  
Group Decision ◽  
Cloud Model ◽  
Decision Makers ◽  
Capacity Investment ◽  
Decision Matrix ◽  
Investment Projects ◽  
Green Capacity

Green capacity investment projects have rapidly emerged involving suppliers, customers, and manufacturing organizations in supply chain systems with environmental challenges. This paper focuses on and identifies both primary strategic and operational elements that will aid managers in evaluating and making risky multi-criteria decisions on green capacity investment projects. We propose a cloud prospect value consensus process consisting of feedback and adjustment mechanisms that provide modification instructions to the corresponding decision makers for a decision matrix based on the cloud model and prospect theory, which considers psychological behavior, disagreements between decision makers, and the ambiguity of linguistic variable assessment across multi-criteria risks. The new model increases the efficiency and accuracy of decision making. To verify the feasibility and validity of the Cloud Prospect Value Consensus Degree based on the Feedback adjustment mechanism, its performance is compared with three state-of-the-art multi-criteria group decision-making methods.

scholarly journals A Multiple Attribute Group Decision Making Approach for Solving Problems with the Assessment of Preference Relations

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Taho Yang ◽  
Yiyo Kuo ◽  
David Parker ◽  
Kuan Hung Chen
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Final Decision ◽  
Decision Matrix ◽  
Preference Relations ◽  
Theoretical Approaches ◽  
Multiple Attribute ◽  
Fuzzy Preference Relations ◽  
Fuzzy Preference

A number of theoretical approaches to preference relations are used for multiple attribute decision making (MADM) problems, and fuzzy preference relations is one of them. When more than one person is interested in the same MADM problem, it then becomes a multiple attribute group decision making (MAGDM) problem. For both MADM and MAGDM problems, consistency among the preference relations is very important to the result of the final decision. The research reported in this paper is based on a procedure that uses a fuzzy preference relations matrix which satisfies additive consistency. This matrix is used to solve multiple attribute group decision making problems. In group decision problems, the assessment provided by different experts may diverge considerably. Therefore, the proposed procedure also takes a heterogeneous group of experts into consideration. Moreover, the methods used to construct the decision matrix and determine the attribution of weight are both introduced. Finally a numerical example is used to test the proposed approach; and the results illustrate that the method is simple, effective, and practical.

scholarly journals Interval-Valued Intuitionistic Fuzzy Multiple Attribute Group Decision Making with Uncertain Weights

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Zhuosheng Jia ◽  
Yingjun Zhang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Collective Decision ◽  
Decision Makers ◽  
Fuzzy Decision ◽  
Decision Matrix ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Interval Valued

The theory of interval-valued intuitionistic fuzzy sets (IVIFSs) has been an impactful and convenient tool in the construction of advanced multiple attribute group decision making (MAGDM) models to counter the uncertainty in the developing complex decision support system. To satisfy much more demands from fuzzy decision making problems, we propose a method to solve the MAGDM problem in which all the information supplied by the decision makers is expressed as interval-valued intuitionistic fuzzy decision matrices where each of the elements is characterized by an interval-valued intuitionistic fuzzy number, and the information about the weights of both decision makers and attributes may be completely unknown or partially known. Firstly, we introduce a consensus-based method to quantify the weights of all decision makers based on all interval-valued intuitionistic fuzzy decision matrices. Secondly, we utilize the interval-valued intuitionistic fuzzy weighted arithmetic (IVIFWA) operator to aggregate all interval-valued intuitionistic fuzzy decision matrices into the collective one. Thirdly, we establish an optimization model to determine the weights of attributes depending on the collective decision matrix and the given attribute weight information. Fourthly, we adopt the weighted correlation coefficient of IVIFSs to rank all the alternatives from the perspective of TOPSIS via the collective decision matrix and the obtained weights of attributes. Finally, some examples are used to illustrate the validity and feasibility of our proposed approach by comparison with some existing models.

scholarly journals Group Decision-Making Based on the VIKOR Method with Trapezoidal Bipolar Fuzzy Information

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1313 ◽  
Author(s):  
Shumaiza ◽  
Muhammad Akram ◽  
Ahmad N. Al-Kenani ◽  
José Carlos R. Alcantud
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Thermal Power ◽  
Decision Makers ◽  
Sources Of Information ◽  
Vikor Method ◽  
Decision Matrix ◽  
Multiple Attribute

The VIKOR methodology stands out as an important multi-criteria decision-making technique. VIKOR stands for “VIekriterijumsko KOmpromisno Rangiranje”, a Serbian term for “multi-criteria optimization and compromise solution”. It has been adapted to sources of information with sundry formats. We contribute to that strand on literature with a design of a new multiple-attribute group decision-making method called the trapezoidal bipolar fuzzy VIKOR method. It consists of a suitable redesign of the VIKOR approach so that it can use information with bipolar configurations. Bipolar fuzzy sets (and numbers) establish a symmetrical trade-off between two judgmental constituents of human thinking. The agents acquire uncertain and vague information in the form of linguistic variables parameterized by trapezoidal bipolar fuzzy numbers. Trapezoidal bipolar fuzzy numbers are considered by decision-makers for assigning the preference information of alternatives with respect to different attributes. Our non-trivial adaptation necessitates several steps. The ranking function of bipolar fuzzy numbers is employed to make a simple decision matrix with real numbers as its entries. Shannon’s entropy concept is applied to evaluate the normalized weights for attributes that may be either partially or completely unknown to the decision-makers. The ordering of the alternatives is obtained by assorting the maximum group utility and the individual regret of the opponent in an ascending manner. For illustration, the proposed technique is applied to two group decision-making problems, namely, the selection of waste treatment methods and the site to plant a thermal power station. A comparison of this method with the trapezoidal bipolar fuzzy TOPSIS method is also presented.

scholarly journals Public Transportation Hub Location with Stochastic Demand: An Improved Approach Based on Multiple Attribute Group Decision-Making

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Sen Liu ◽  
Zhilan Song ◽  
Shuqi Zhong
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Public Transportation ◽  
Group Decision ◽  
Numerical Study ◽  
Hub Location ◽  
Hub Location Problem ◽  
The Public ◽  
Multiple Attribute ◽  
Qualitative Factors

Urban public transportation hubs are the key nodes of the public transportation system. The location of such hubs is a combinatorial problem. Many factors can affect the decision-making of location, including both quantitative and qualitative factors; however, most current research focuses solely on either the quantitative or the qualitative factors. Little has been done to combine these two approaches. To fulfill this gap in the research, this paper proposes a novel approach to the public transportation hub location problem, which takes both quantitative and qualitative factors into account. In this paper, an improved multiple attribute group decision-making (MAGDM) method based on TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and deviation is proposed to convert the qualitative factors of each hub into quantitative evaluation values. A location model with stochastic passenger flows is then established based on the above evaluation values. Finally, stochastic programming theory is applied to solve the model and to determine the location result. A numerical study shows that this approach is applicable and effective.

CPT-MABAC method for spherical fuzzy multiple attribute group decision making and its application to green supplier selection

2021 ◽  
pp. 1-11
Author(s):  
Huiyuan Zhang ◽  
Guiwu Wei ◽  
Xudong Chen
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Comparison Method ◽  
Entropy Method ◽  
Decision Makers ◽  
Green Supplier Selection ◽  
Multiple Attribute ◽  
Psychological Perceptions

The green supplier selection is one of the popular multiple attribute group decision making (MAGDM) problems. The spherical fuzzy sets (SFSs) can fully express the complexity and fuzziness of evaluation information for green supplier selection. Furthermore, the classic MABAC (multi-attributive border approximation area comparison) method based on the cumulative prospect theory (CPT-MABAC) is designed, which is an optional method in reflecting the psychological perceptions of decision makers (DMs). Therefore, in this article, we propose a spherical fuzzy CPT-MABAC (SF-CPT-MABAC) method for MAGDM issues. Meanwhile, considering the different preferences of DMs to attribute sets, we obtain the objective weights of attributes through entropy method. Focusing on the current popular problems, this paper applies the proposed method for green supplier selection and proves for green supplier selection based on SF-CPT-MABAC method. Finally, by comparing existing methods, the effectiveness of the proposed method is certified.

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