A Preference Structure in Multi-attribute Decision Making – an Algorithmic Approach Based on Hesitant Fuzzy Sets

2021 ◽  
Author(s):  
Bhaba Krishna Mohanty ◽  
Eshika Aggarwal
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Pairwise Comparison ◽  
Preference Structure ◽  
Hesitant Fuzzy Sets ◽  
Pairwise Comparison Matrix ◽  
Algorithmic Approach ◽  
Fuzzy Environment ◽  
Eigen Value ◽  
Multi Attribute Decision Making

Abstract This paper introduces a new methodology for solving Multi-Attribute Decision Making (MADM) problems under hesitant fuzzy environment. The uncertainty in Hesitant Fuzzy Elements (HFE) are derived by means of entropy. The resulting uncertainty is subsequently used in HFE to derive a single representative value (RV) of alternatives in each attribute. Our work transforms the RVs into their linguistic counterparts and then formulates a methodology for pairwise comparison of the alternatives via their linguistically defines RVs. The Eigen vector corresponding to maximum Eigen value of the pairwise comparison matrix prioritize the alternatives in each attribute. The priority vectors of the alternatives are aggregated to derive the weights of the attributes using Quadratic programming. The weighted aggregation of the attribute values provides the ranking of the alternatives in MADM. An algorithm is written to validate the procedure developed. The proposed methodology is compared with similar existing methods and the advantages of our method are presented. The robustness of our methodology is demonstrated through sensitivity analysis. To highlight the procedure a car purchasing problem is illustrated.

scholarly journals Application of the AHP-BWM Model for Evaluating Driver Behavior Factors Related to Road Safety: A Case Study for Budapest

Symmetry ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 243 ◽  
Author(s):  
Sarbast Moslem ◽  
Danish Farooq ◽  
Omid Ghorbanzadeh ◽  
Thomas Blaschke
Keyword(s):  
Decision Making ◽  
Road Safety ◽  
Driver Behavior ◽  
Pairwise Comparison ◽  
Scientific Data ◽  
Analytic Hierarchy ◽  
Pairwise Comparison Matrix ◽  
Proposed Model ◽  
Decision Making Problem ◽  
Complex Decision Making

The use of driver behavior has been considered a complex way to solve road safety complications. Car drivers are usually involved in various risky driving factors which lead to accidents where people are fatally or seriously injured. The present study aims to dissect and rank the significant driver behavior factors related to road safety by applying an integrated multi-criteria decision-making (MCDM) model, which is structured as a hierarchy with at least one 5 × 5 (or bigger) pairwise comparison matrix (PCM). A real-world, complex decision-making problem was selected to evaluate the possible application of the proposed model (driver behavior preferences related to road safety problems). The application of the analytic hierarchy process (AHP) alone, by precluding layman participants, might cause a loss of reliable information in the case of the decision-making systems with big PCMs. Evading this tricky issue, we used the Best Worst Method (BWM) to make the layman’s evaluator task easier and timesaving. Therefore, the AHP-BWM model was found to be a suitable integration to evaluate risky driver behavior factors within a designed three-level hierarchical structure. The model results found the most significant driver behavior factors that influence road safety for each level, based on evaluator responses on the driver behavior questionnaire (DBQ). Moreover, the output vector of weights in the integrated model is more consistent, with results for 5 × 5 PCMs or bigger. The proposed AHP-BWM model can be used for PCMs with scientific data organized by traditional means.

scholarly journals A Novel Decision-Making Approach under Complex Pythagorean Fuzzy Environment

2019 ◽  
Vol 24 (3) ◽  
pp. 73 ◽  
Author(s):  
Muhammad Akram ◽  
Sumera Naz
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Research Study ◽  
Regular Graphs ◽  
Pythagorean Fuzzy Set ◽  
Improvement Project ◽  
Fuzzy Environment ◽  
Fuzzy Graphs ◽  
Technology Improvement ◽  
Multi Attribute Decision Making

A complex Pythagorean fuzzy set (CPFS) is an extension of a Pythagorean fuzzy set that is used to handle the vagueness with the degrees whose ranges are enlarged from real to complex subset with unit disc. In this research study, we propose the innovative concept of complex Pythagorean fuzzy graphs (CPFGs). Further, we present the concepts of regular and edge regular graphs in a complex Pythagorean fuzzy environment. Moreover, we develop a complex Pythagorean fuzzy graph based multi-attribute decision making an approach to handling the situations in which the graphic structure of attributes is obscure. A numerical example concerning information technology improvement project selection is utilized to illustrate the availability of the developed approach.

scholarly journals Utilization of AHP-MAUT Method to Determine the Country of Exhibition Abroad in Batik Hatta Boutique

2021 ◽  
Vol 5 (02) ◽  
pp. 52-56
Author(s):  
Saifur Rohman Cholil ◽  
Tria Ardianita
Keyword(s):  
Decision Making ◽  
Rank Correlation ◽  
Pairwise Comparison ◽  
Hierarchical Level ◽  
Spearman Rank Correlation ◽  
Ahp Method ◽  
Pairwise Comparison Matrix ◽  
Spearman Rank ◽  
Comparison Matrix ◽  
A Value

This research was conducted with the aim of helping decide the destination country for overseas exhibitions at the Batik Hatta Boutique. By knowing all the data and information of a country, boutique owners can decide which country to visit in the batik exhibition. Because if you attend the cast in all countries, there will be overruns in costs. The methods used are AHP and MAUT. The AHP method is used as a weighting using a linguistic value scale. Weights are obtained from the pairwise comparison matrix between two elements of all elements that occur at the same hierarchical level. The MAUT method is used to determine the importance of each alternative for the ranking process. The results of this study indicate that Cambodia was chosen as the location to be visited for the batik exhibition. The results of the validation using the Spearman Rank correlation comparison obtained a value of 0.951 meaning that this method can be used as a 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 Matrix of pairwise comparison: decision making with the analytic network process

2019 ◽  
Vol 110 ◽  
pp. 02042
Author(s):  
Aliya Akhmadullina ◽  
Svetlana Vasilyeva ◽  
Tatyana Yakovleva ◽  
Svetlana Vopiyashina ◽  
Raisa Kraineva
Keyword(s):  
Decision Making ◽  
Environmental Planning ◽  
Pairwise Comparison ◽  
Multicriteria Decision Making ◽  
Analytic Network Process ◽  
Analytic Hierarchy ◽  
Pairwise Comparison Matrix ◽  
Network Process ◽  
Qualitative Factors ◽  
The Right

This article describes a method for analyzing hierarchies; identifies the problems with inconsistent judgments. The proof is given that the most effective tool allowing one to make the right decisions with inconsistencies is the introduction of the eigenvector on environmental planning and management. The Analytic Hierarchy Process (AHP) is a method for decision making, which includes qualitative factors. In this method, ratio scales are obtained from ordinal scales, which are derived from individual judgments for qualitative factors using the pairwise comparison matrix. This paper describes the applicability of a multicriteria decision-making method, specifically, the analytic network process.

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