MULTI-ATTRIBUTE DECISION MAKING BASED ON LABEL SEMANTICS

2008 ◽  
Vol 16 (supp02) ◽  
pp. 69-86 ◽  
Author(s):  
JONATHAN LAWRY ◽  
HONGMEI HE
Keyword(s):  
Decision Making ◽  
Decision Trees ◽  
Information Aggregation ◽  
Multiple Attribute Decision Making ◽  
Probabilistic Uncertainty ◽  
Functional Relationships ◽  
Multiple Attribute ◽  
Label Semantics ◽  
Multi Attribute Decision Making ◽  
High Level

We propose label semantics as an integrated representation framework for probabilistic uncertainty and fuzziness in multiple-attribute decision making problems. Linguistic attribute hierarchies are then introduced as a means of modelling the complex and often imprecise functional relationships between low-level attributes or measurements and high-level decision or classification variables. Within this framework we introduce linguistic decision trees as a tool for information aggregation in multi-attribute decision problems and describe the process of information propagation through a hierarchy of linked decision trees. In addition, we consider the ranking of different alternatives or examples based on their linguistic descriptions of a high-level utility variable. Finally, we discuss how linguistic decision trees embedded in attribute hierarchies can be learnt from data.

scholarly journals Dual Generalized Nonnegative Normal Neutrosophic Bonferroni Mean Operators and Their Application in Multiple Attribute Decision Making

Information ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 201 ◽  
Author(s):  
Jiongmei Mo ◽  
Han-Liang Huang
Keyword(s):  
Decision Making ◽  
Score Function ◽  
Information Aggregation ◽  
Multiple Attribute Decision Making ◽  
Ranking Method ◽  
Bonferroni Mean ◽  
Operational Laws ◽  
Multiple Attribute ◽  
Geometric Bonferroni Mean ◽  
Neutrosophic Number

For multiple attribute decision making, ranking and information aggregation problems are increasingly receiving attention. In a normal neutrosophic number, the ranking method does not satisfy the ranking principle. Moreover, the proposed operators do not take into account the correlation between any aggregation arguments. In order to overcome the deficiencies of the existing ranking method, based on the nonnegative normal neutrosophic number, this paper redefines the score function, the accuracy function, and partial operational laws. Considering the correlation between any aggregation arguments, the dual generalized nonnegative normal neutrosophic weighted Bonferroni mean operator and dual generalized nonnegative normal neutrosophic weighted geometric Bonferroni mean operator were investigated, and their properties are presented. Here, these two operators are applied to deal with a multiple attribute decision making problem. Example results show that the proposed method is effective and superior.

Set Pair Analysis Method of Containing Target Constraint Mixed Interval Multi-Attribute Decision-Making

2012 ◽  
Vol 226-228 ◽  
pp. 2222-2226 ◽  
Author(s):  
Wen Sheng Lü ◽  
Bin Zhang
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Set Pair Analysis ◽  
Analysis Theory ◽  
Multiple Attribute ◽  
Complex Decision Making ◽  
Multi Attribute Decision Making ◽  
Interval Type ◽  
Pair Analysis ◽  
Attribute Value

In view of target attribute value for different sector number, moreover, also attaches a target constraint condition kind of mix sector multi-attribute decision making question, this paper presents set pair analysis decision-making method. Firstly this paper puts forward three typical interval type attribute value representation; Then using set pair analysis theory, the interval type attribute value unified convert the correlate form, Finally has given complex decision-making criterion function, which collected Conformity degree criteria and Criteria for membership degree. Through the construction plan changes decision-making example analysis shows that this method is a simple and effective method for solving multiple attribute decision making.

scholarly journals A Novel q-Rung Dual Hesitant Fuzzy Multi-Attribute Decision-Making Method Based on Entropy Weights

Entropy ◽  
2021 ◽  
Vol 23 (10) ◽  
pp. 1322
Author(s):  
Yaqing Kou ◽  
Xue Feng ◽  
Jun Wang
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Entropy Measure ◽  
Fuzzy Environment ◽  
Multiple Attribute ◽  
Special Cases ◽  
Multi Attribute Decision Making ◽  
Novel Method ◽  
And Performance

In this paper, a new multiple attribute decision-making (MADM) method under q-rung dual hesitant fuzzy environment from the perspective of aggregation operators is proposed. First, some aggregation operators are proposed for fusing q-rung dual hesitant fuzzy sets (q-RDHFSs). Afterwards, we present properties and some desirable special cases of the new operators. Second, a new entropy measure for q-RDHFSs is developed, which defines a method to calculate the weight information of aggregated q-rung dual hesitant fuzzy elements. Third, a novel MADM method is introduced to deal with decision-making problems under q-RDHFSs environment, wherein weight information is completely unknown. Finally, we present numerical example to show the effectiveness and performance of the new method. Additionally, comparative analysis is conducted to prove the superiorities of our new MADM method. This study mainly contributes to a novel method, which can help decision makes select optimal alternatives when dealing with practical MADM problems.

scholarly journals Hesitant Triangular Fuzzy Information Aggregation Operators Based on Bonferroni Means and Their Application to Multiple Attribute Decision Making

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Chunyong Wang ◽  
Qingguo Li ◽  
Xiaoqiang Zhou ◽  
Tian Yang
Keyword(s):  
Decision Making ◽  
Information Aggregation ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Fuzzy Information ◽  
Fuzzy Environment ◽  
Operational Laws ◽  
Multiple Attribute ◽  
Special Cases ◽  
Fuzzy Aggregation

We investigate the multiple attribute decision-making (MADM) problems with hesitant triangular fuzzy information. Firstly, definition and some operational laws of hesitant triangular fuzzy elements are introduced. Then, we develop some hesitant triangular fuzzy aggregation operators based on Bonferroni means and discuss their basic properties. Some existing operators can be viewed as their special cases. Next, we apply the proposed operators to deal with multiple attribute decision-making problems under hesitant triangular fuzzy environment. Finally, an illustrative example is given to show the developed method and demonstrate its practicality and effectiveness.

scholarly journals Possibility Neutrosophic Cubic Sets and Their Application to Multiple Attribute Decision Making

Symmetry ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 269 ◽  
Author(s):  
Huiling Xue ◽  
Xiaotong Yang ◽  
Chunfang Chen
Keyword(s):  
Decision Making ◽  
Binary Operation ◽  
Score Function ◽  
Multiple Attribute Decision Making ◽  
Membership Degree ◽  
Neutrosophic Sets ◽  
Important Indicator ◽  
Multiple Attribute ◽  
Decision Making Problem ◽  
Multi Attribute Decision Making

The neutrosophic cubic sets are an extension of the cubic sets to the neutrosophic sets. It contains three variables, which respectively represent the membership degree, non-membership degree and uncertainty of the element to the set. The score function is an important indicator in the multi-attribute decision-making problem. In this paper, we consider the possibility that an element belongs to a set and put forward the concept of possibility neutrosophic cubic sets. On this basis, we introduce some related concepts and give the binary operation of possibility neutrosophic cubic sets and use specific examples to supplement the corresponding definition. Meanwhile, a decision-making method based on the score function of possibility neutrosophic cubic sets is proposed and a numerical example is given to illustrate the effectiveness of the proposed method.

Classifying the Level of Economic of Citizen Using Fuzzy Multiple Attribute Decision Making

2019 ◽  
Vol 892 ◽  
pp. 88-93
Author(s):  
Muhamad Muslihudin ◽  
Rita Irviani ◽  
Prayugo Khoir ◽  
Andino Maseleno ◽  
K. Shankar ◽  
...  
Keyword(s):  
Decision Making ◽  
Social Insurance ◽  
Banking Sector ◽  
Multiple Attribute Decision Making ◽  
Economic Assistance ◽  
The People ◽  
Multiple Attribute ◽  
The Government ◽  
Simple Additive Weighting ◽  
High Level

Economics is the first supply for the survival of a country, especially in the development, development and progress. The more developed a country is the better economic growth. Indonesia including the user databases on the economy, especially in the banking sector and the government. Government as the manager of the country's economy in order to make extra efforts of the people and citizens can get considerable economic assistance through various operations conducted by the government such as the division of poor rice and BPJS card. BPJS stands for Badan Penyelenggara Jaminan Sosial (Social Insurance Administration Organization). By doing classifying economic levels using Fuzzy Multiple Attribute Decision Making (FMADM) methods (Simple Additive Weighting) meant that applications created can be used as a tool to suppress errors and improve accuracy by minimizing the possibility of such a wrong target or targets. The application uses the input in the form of data that has a high level of security to be forged such as: proof of payment of electricity bills, vehicle tax, and property tax. Data from the family card to input the number of people staying. The results are sorted according emerged from the lowest to the highest. The calculations were already system and by calculation that has been designed is expected to work as expected.

Multi-Objective Optimization Design of Steel Frames Based on Multiple Attribute Decision-Making Method

2013 ◽  
Vol 368-370 ◽  
pp. 830-837
Author(s):  
Mao Qiao Cui ◽  
Hai Yan Huang ◽  
Fu Lai Wang ◽  
Yong Qiu
Keyword(s):  
Decision Making ◽  
Optimization Design ◽  
Intuitionistic Fuzzy Set ◽  
Optimal Solution ◽  
Multiple Attribute Decision Making ◽  
Optimization Strategy ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Multiple Attribute ◽  
High Level

This paper describes in detail a multi-objective optimization strategy and decision-making method in the process of steel frame optimization design. A step-by-step analysis process integrating optimization algorithm and model analysis is proposed to solve the present problem. A multi-objective algorithm method using fast Non-dominated Sorting Genetic Algorithm is employed to obtain the Pareto-optimal solution set through an evolutionary optimization process. A high-level multiple attribute decision-making method based on intuitionistic fuzzy set theory is adopted to rank these solutions from the best to worst, and to determine the best solution. An example is used to demonstrate the proposed optimization model and decision-making method.

scholarly journals Multiple Attribute Decision Making Based on Linguistic Generalized Weighted Heronian Mean

Symmetry ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1191
Author(s):  
Ximei Hu ◽  
Shuxia Yang ◽  
Ya-Ru Zhu
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Multiple Attribute ◽  
Theoretical Significance ◽  
Multi Attribute Decision Making ◽  
Parameter Symmetry ◽  
Heronian Mean

In actual multiple attribute decision making, people often use language to evaluate attributes of the object, and sometimes there are associations between the attributes. Therefore, the study of multiple attribute decision making with language as attributes and associations between attributes is of great theoretical significance and practical value. The Heronian mean is not only an operator which reflects the associations between attributes, but also has excellent properties, including idempotency, monotonicity, boundedness, parameter symmetry, and alternate symmetry. In this paper, firstly a new linguistic generalized weighted Heronian mean (LGWHM) was provided, and its properties including idempotency, monotonicity, boundedness, and limit were studied. Then, a new three-parameter linguistic generalized weighted Heronian mean (TPLGWHM) and its idempotency, monotonicity, and boundedness properties were proposed. Finally, multi-attribute decision making methods based on the new linguistic generalized weighted Heronian mean were given, and an example was analyzed and compared with other methods.

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