scholarly journals Dombi Aggregation Operators of Linguistic Cubic Variables for Multiple Attribute Decision Making

Information ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 188 ◽  
Author(s):  
Xueping Lu ◽  
Jun Ye
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Optimal Choice ◽  
Decision Makers ◽  
Linguistic Variable ◽  
Operational Parameter ◽  
Arithmetic Average ◽  
Weighted Arithmetic ◽  
Multiple Attribute ◽  
Dombi Operations

A linguistic cubic variable (LCV) is comprised of interval linguistic variable and single-valued linguistic variable. An LCV contains decision-makers’ uncertain and certain linguistic judgments simultaneously. The advantage of the Dombi operators contains flexibility due to its changeable operational parameter. Although the Dombi operations have been extended to many studies to solve decision-making problems; the Dombi operations are not used for linguistic cubic variables (LCVs) so far. Hence, the Dombi operations of LCVs are firstly presented in this paper. A linguistic cubic variable Dombi weighted arithmetic average (LCVDWAA) operator and a linguistic cubic variable Dombi weighted geometric average (LCVDWGA) operator are proposed to aggregate LCVs. Then a multiple attribute decision making (MADM) method is developed in LCV setting on the basis of LCVDWAA and LCVDWGA operators. Finally, two illustrative examples about the optimal choice problems demonstrate the validity and the application of this method.

scholarly journals Dynamic Hybrid Multiple Attribute Decision-Making Problem Based on Reference Point Adaptation

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Wei-Min Ma ◽  
Hui Zhang ◽  
Bing-Zhen Sun ◽  
Neng-Li Wang ◽  
Hai-Yan Zhao
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Reference Point ◽  
Multiple Attribute Decision Making ◽  
Optimal Choice ◽  
Reference Points ◽  
Decision Makers ◽  
Multiple Attribute ◽  
Decision Making Problem ◽  
Dynamic Hybrid

Individuals’ decision-making depends on reference points in prospect theory. This research considers the bounded rationality of decision makers and constructs a dynamic hybrid multiple attribute decision-making (DHMADM) model. Unlike existing models, the DHMADM model focuses on dynamic reference point, which has been proven in prospect theory. This research presents the effects of reference point adaptation on decision-making through model calculation. The optimal choice of decision makers changed with the change of the reference point in the DHMADM model. By experiment, we found that the DHMADM model considering reference point adaptation can more accurately express the final choice of decision makers than models only considering the static reference point.

Material Selection Using a Novel Multiple Attribute Decision Making Method

2012 ◽  
pp. 252-266
Author(s):  
R. V. Rao ◽  
B. K. Patel
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Decision Maker ◽  
Design Process ◽  
Material Selection ◽  
Multiple Attribute Decision Making ◽  
Decision Makers ◽  
Selection Problem ◽  
Multiple Attribute ◽  
Selection Of

Selection of a most appropriate material is a very important task in design process of every product. There is a need for simple, systematic, and logical methods or mathematical tools to guide decision makers in considering a number of selection attributes and their interrelations and in making right decisions. This paper proposes a novel multiple attribute decision making (MADM) method for solving the material selection problem. The method considers the objective weights of importance of the attributes as well as the subjective preferences of the decision maker to decide the integrated weights of importance of the attributes. Furthermore, the method uses fuzzy logic to convert the qualitative attributes into the quantitative attributes. Two examples are presented to illustrate the potential of the proposed method.

scholarly journals Some Novel Picture 2-Tuple Linguistic Maclaurin Symmetric Mean Operators and Their Application to Multiple Attribute Decision Making

Symmetry ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 943
Author(s):  
Min Feng ◽  
Yushui Geng
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Linguistic Variable ◽  
Maclaurin Symmetric Mean ◽  
Multiple Attribute ◽  
Picture Fuzzy Set ◽  
Input Parameters ◽  
Cognitive Information

When solving multiple attribute decision making (MADM) problems, the 2-tuple linguistic variable is an effective tool that can not only express complex cognitive information but also prevent loss of information in calculation. The picture fuzzy set (PFS) has three degrees and has more freedom to express cognitive information. In addition, Archimedean t-conorm and t-norm (ATT) can generalize most existing t-conorms and t-norms and Maclaurin symmetric mean (MSM) operators can catch the relationships among the multi-input parameters. Therefore, we investigate several novel aggregation operators, such as the picture 2-tuple linguistic MSM (2TLMSM) operator based on the ATT (ATT-P2TLMSM) and the picture 2-tuple linguistic generalized MSM (2TLGMSM) operator based on ATT (ATT-P2TLGMSM). Considering that the input parameters have different importance, we proposed picture 2-tuple linguistic weighted MSM (2TLWMSM) operators based on ATT (ATT-P2TLWMSM) and picture 2-tuple linguistic weighted generalized MSM (2TLWGMSM) operators based on ATT (ATT-P2TLWGMSM). Finally, a MADM method is introduced, and an expositive example is presented to explain the availability and applicability of the developed operators and methods.

scholarly journals Selection of Industrial Robots for Automation Applications in Multiple Attribute Decision Making Environment using the Analytical Network Process

2018 ◽  
Vol 7 (3.12) ◽  
pp. 392 ◽  
Author(s):  
N Rishi Kanth ◽  
A Srinath ◽  
J Suresh Kumar
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Industrial Robots ◽  
Decision Makers ◽  
Analytical Network Process ◽  
Multiple Attribute ◽  
Network Process ◽  
Complex Relationships ◽  
Robot Selection ◽  
Selection Of

Analytical Network process (ANP), is applied here as a decision making technique for the selection of appropriate robots for industrial and automation applications. The core motivation of applying, in particular, the ANP technique is that robot selection is dependent upon a number of attributes and criteria which have strong influences/interdependencies upon each other. The ANP, as a multiple attribute decision making (MADM) technique for robot selection, captures the effects of these cross hierarchical dependencies, and appropriately maps the influences within the clusters and between the various alternatives. Simultaneously, the technique does not include the assumption of independence of higher-level elements from lower level elements and about the independence of the elements within a level. First, a set of attributes, which influence the selection of the robots, are identified. Next, using the various steps of ANP, viz., pair wise comparisons matrices and priority vectors determination and the development of the super-matrix the global weights of the attributes with respect to other attributes are determined. The final alternatives are then rated as per the graduated weights of the respective attributes. Thus, a comprehensive solution towards selection of robots enabling the decision-makers to suitably understand the complex relationships of the relevant qualitative and quantitative attributes in the decision-making is obtained. The technique is also illustrated using detailed analysis for a specific case of decision making between three robot suppliers and selection of appropriate robot from alternatives. In order to get more insight into relationships among various attributes and their effect on decision makers, the sensitivity analysis of the results with respect to determinant level attributes is carried out.   

scholarly journals Decision-Maker’s Risk Preference Based Intuitionistic Fuzzy Multiattribute Decision-Making and Its Application in Robot Enterprises Investment

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Liandong Zhou ◽  
Qifeng Wang
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Weight Vector ◽  
Multiple Attribute Decision Making ◽  
Decision Makers ◽  
Research Papers ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Fuzzy Weight

At present, the utilization of hesitation information of intuitionistic fuzzy numbers is insufficient in many methods which were proposed to solve the intuitionistic fuzzy multiple attribute decision-making problems. And also there exist some flaws in the intuitionistic fuzzy weight vector constructions in many research papers. In order to solve these insufficiencies, this paper defined three construction equations of weight vectors based on the risk preferences of decision-makers. Then we developed an intuitionistic fuzzy dependent hybrid weighted operator (IFDHW) and proposed an intuitionistic fuzzy multiattribute decision-making method. Finally, the effectiveness of this method is verified by a robot manufacturing investment example.

Human Immunodeficiency Virus (HIV) infection model based on triangular neutrosophic cubic hesitant fuzzy number

2019 ◽  
Vol 12 (05) ◽  
pp. 1950055 ◽  
Author(s):  
Fazli Amin ◽  
Aliya Fahmi
Keyword(s):  
Decision Making ◽  
Human Immunodeficiency Virus ◽  
Fuzzy Number ◽  
Score Function ◽  
Multiple Attribute Decision Making ◽  
Infection Model ◽  
Weighted Arithmetic ◽  
Multiple Attribute ◽  
Immunodeficiency Virus ◽  
Hiv Infection Model

In this paper, we define the basic concept of triangular neutrosophic cubic hesitant fuzzy number and their properties. We develop a triangular neutrosophic cubic hesitant fuzzy ordered weighted arithmetic averaging (TNCHFOWAA) operator and a triangular neutrosophic cubic hesitant fuzzy ordered weighted geometric averaging (TNCHFOWGA) operator to aggregate triangular neutrosophic cubic hesitant fuzzy number (TNCHFN) information and investigate their properties. Furthermore, a multiple attribute decision-making method based on the TNCHFOWAA operator and triangular neutrosophic cubic hesitant fuzzy ordered weighted geometric (TNCHFOWG) operator and the score function of TNCHFN is established under a TNCHFN environment. Finally, an illustrative example of investment alternatives is given to demonstrate the application and effectiveness of the developed approach.

scholarly journals A New Fuzzy Multiple Attribute Decision Making Method Based on the Utility Transformation Functions

Symmetry ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 418
Author(s):  
Yuting Zuo ◽  
Chunfang Chen
Keyword(s):  
Decision Making ◽  
Utility Theory ◽  
Weighted Average ◽  
Multiple Attribute Decision Making ◽  
Decision Makers ◽  
Linguistic Information ◽  
Operational Laws ◽  
Multiple Attribute ◽  
Transformation Functions ◽  
The Difference

The 2-tuple linguistic information model (2TLIM) is a useful tool to avoid the loss of information, which has been widely adapted in the study of the multiple attribute decision making (MADM) problem. However, there is a limitation, the limitation is that the difference between the neighboring 2-tuple linguistic information is fixed regardless of the decision-makers’ attitude. In this paper, we define the utility transformation functions based on the 2-tuple linguistic utility to overcome the drawback. Firstly, by introducing the economic utility theory, the 2-tuple linguistic utility is defined, the 2-tuple linguistic utility parameter (2TLUP) and the 2-tuple linguistic marginal utility (2TLMU) are constructed to achieve the measurement of the decision-makers’ attitude. The utility transformation functions are developed on the decision-makers’ attitude. Secondly, the 2-tuple linguistic operational laws are presented with the extended Hamacher T-norm (TN) and T-conorm (TC). Subsequently, we propose the 2-tuple linguistic utility weighted average (2TLUWA) operator and the method of MADM. Lastly, the application and the comparison with the existing methods are summarized to verify the practicality and advantages of the proposed method of MADM.

scholarly journals An Approach to Linguistic Multiple Attribute Decision-Making Based on Unbalanced Linguistic Generalized Heronian Mean Aggregation Operator

2018 ◽  
Vol 2018 ◽  
pp. 1-25 ◽  
Author(s):  
Bing Han ◽  
Huayou Chen ◽  
Jiaming Zhu ◽  
Jinpei Liu
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Low Carbon ◽  
Weighted Arithmetic ◽  
Multiple Attribute ◽  
Linguistic Assessment ◽  
Linguistic Assessment Information ◽  
Heronian Mean ◽  
Generalized Arithmetic

This paper proposes an approach to linguistic multiple attribute decision-making problems with interactive unbalanced linguistic assessment information by unbalanced linguistic generalized Heronian mean aggregation operators. First, some generalized Heronian mean aggregation operators with unbalanced linguistic information are proposed, involving the unbalanced linguistic generalized arithmetic Heronian mean operator and the unbalanced linguistic generalized geometric Heronian mean operator. For the situation that the input arguments have different degrees of importance, the unbalanced linguistic generalized weighted arithmetic Heronian mean operator and the unbalanced linguistic generalized weighted geometric Heronian mean operator are developed. Then we investigate their properties and some particular cases. Finally, the effectiveness and universality of the developed approach are illustrated by a low-carbon tourist instance and comparison analysis. A sensitivity analysis is performed as well to test the robustness of proposed methods.

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