scholarly journals A Multi-Attribute Decision-Making Algorithm Using Q-Rung Orthopair Power Bonferroni Mean Operator and Its Application

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1240 ◽  
Author(s):  
Ping He ◽  
Zaoli Yang ◽  
Bowen Hou
Keyword(s):  
Decision Making ◽  
Influence Factors ◽  
Uncertain Information ◽  
Fuzzy Information ◽  
Bonferroni Mean ◽  
Decision Making Problem ◽  
Multi Attribute Decision Making ◽  
New Type ◽  
Multiple Variables ◽  
Internal Relationship

The process of decision-making is subject to various influence factors and environmental uncertainties, which makes decision become a very complex task. As a new type of decision processing tool, the q-rung orthopair fuzzy sets can effectively deal with complex uncertain information arising in the decision process. To this end, this study proposes a new multi-attribute decision-making algorithm based on the power Bonferroni mean operator in the context of q-rung orthopair fuzzy information. In this method, in view of multi-attribute decision-making problem of internal relationship between multiple variables and extreme evaluation value, the Bonferroni mean operator is combined with power average operator. Then, the integrated operator is introduced into the q-rung orthopair fuzzy set to develop a new q-rung orthopair power Bonferroni mean operator, and some relevant properties of this new operator are discussed. Secondly, a multi-attribute decision-making method is established based on this proposed operator. Finally, the feasibility and superiority of our method are testified via a numerical example of investment partner selection in the tourism market.

Spherical uncertain linguistic Hamacher aggregation operators and their application on achieving consistent opinion fusion in group decision making

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Muhammad Qiyas ◽  
Saleem Abdullah ◽  
Muhammad Naeem
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Aggregation Operator ◽  
Aggregation Operators ◽  
Content Type ◽  
Operational Laws ◽  
Decision Making Problem ◽  
Multi Attribute Decision Making ◽  
New Type

PurposeThe aim of this research is to establish a new type of aggregation operator based on Hamacher operational law of spherical uncertain linguistic numbers (SULNs).Design/methodology/approachFirst, the authors define spherical uncertain linguistic sets and develop some operational laws of SULNs. Furthermore, the authors extended these operational laws to the aggregation operator and developed spherical uncertain linguistic Hamacher averaging and geometric aggregation operators.FindingsThe authors were limited in achieving a consistent opinion on the fusion in group decision-making problem with the SULN information.Originality/valueIn order to give an application of the introduced operators, the authors first constrict a system of multi-attribute decision-making algorithm.

An extension on PROMETHEE based on the typical hesitant fuzzy sets to solve multi-attribute decision-making problem

Kybernetes ◽  
2016 ◽  
Vol 45 (8) ◽  
pp. 1213-1231 ◽  
Author(s):  
Amin Mahmoudi ◽  
Soheil Sadi-Nezhad ◽  
Ahmad Makui ◽  
Mohammad Reza Vakili
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Distance Functions ◽  
Fuzzy Information ◽  
Content Type ◽  
Decision Making Problem ◽  
Promethee Method ◽  
Multi Attribute Decision Making ◽  
Fuzzy Linguistic ◽  
Practical Implications

Purpose The purpose of this paper is to extend the PROMETHEE method under typical hesitant fuzzy information for solving multi-attribute decision-making problem in which there is hesitancy among experts. Design/methodology/approach Different aggregation and distance functions were developed to deal with HFS. But it is rational that different operators applying in existing methods can produce different results. Also, it is difficult for decision makers to select suitable operators. To address the drawback, this paper develops the PROMETHEE method as an outranking approach to accommodate hesitant fuzzy information. Since the proposed method is constructed on the basis of the pair-wise comparisons, it is independent of the aggregation and distance functions. Findings To demonstrate the efficiency and accuracy of the proposed method, the authors provide a numerical example and a comparative analysis. The results indicate that outranking-based methods suggest a better ranking than the aggregation- and distance-based methods. Research limitations/implications The proposed approach does not consider the hesitant fuzzy linguistic information decision-making problem. Practical implications The proposed approach can be applied in many group decision-making problems in which there is hesitancy among experts. Originality/value This paper proposes an extension on PROMETHEE method under hesitant fuzzy information, which has not been reported in the existing academic literature.

scholarly journals Generalized Fuzzy Soft Power Bonferroni Mean Operators and Their Application in Decision Making

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 810
Author(s):  
Zitai Xu ◽  
Chunfang Chen ◽  
Yutao Yang
Keyword(s):  
Decision Making ◽  
Soft Power ◽  
Original Data ◽  
Decision Makers ◽  
Decision Making Process ◽  
Software Selection ◽  
Decision Method ◽  
Bonferroni Mean ◽  
Special Cases ◽  
Multi Attribute Decision Making

In decision-making process, decision-makers may make different decisions because of their different experiences and knowledge. The abnormal preference value given by the biased decision-maker (the value that is too large or too small in the original data) may affect the decision result. To make the decision fair and objective, this paper combines the advantages of the power average (PA) operator and the Bonferroni mean (BM) operator to define the generalized fuzzy soft power Bonferroni mean (GFSPBM) operator and the generalized fuzzy soft weighted power Bonferroni mean (GFSWPBM) operator. The new operator not only considers the overall balance between data and information but also considers the possible interrelationships between attributes. The excellent properties and special cases of these ensemble operators are studied. On this basis, the idea of the bidirectional projection method based on the GFSWPBM operator is introduced, and a multi-attribute decision-making method, with a correlation between attributes, is proposed. The decision method proposed in this paper is applied to a software selection problem and compared to the existing methods to verify the effectiveness and feasibility of the proposed method.

Decision Method of Optimal Investment Enterprise Selection under Uncertain Information Environment

2015 ◽  
Vol 4 (1) ◽  
pp. 33-42 ◽  
Author(s):  
Xiaoyong Liao
Keyword(s):  
Decision Making ◽  
Optimal Investment ◽  
Information Environment ◽  
Investment Risk ◽  
Uncertain Information ◽  
Fuzzy Information ◽  
Selection Decision ◽  
Deviation Degree ◽  
Grey Number ◽  
Decision Making Model

To select an optimal investment enterprise is the key to effectively reduce the investment risk for an investment company. In this paper, the author studies the problem of optimal investment enterprise selection decision under uncertain information environment (fuzzy information and grey information coexist), and present a fuzzy grey multi-attribute group decision making model to select the optimal investment enterprise. In this model, the author defines the concept and operations of fuzzy grey number, and present a ranking method based on fuzzy grey deviation degree to rank the alternative investment enterprises. The author also gives an application example of selecting optimal investment enterprise to highlight the implementation, availability, and feasibility of the proposed decision making model.

scholarly journals TOPSIS Method Based on Complex Spherical Fuzzy Sets with Bonferroni Mean Operators

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1739
Author(s):  
Zeeshan Ali ◽  
Tahir Mahmood ◽  
Miin-Shen Yang
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Unit Interval ◽  
Polar Coordinates ◽  
Topsis Method ◽  
Bonferroni Mean ◽  
Operational Laws ◽  
Special Cases ◽  
Order Preference ◽  
Multi Attribute Decision Making

The theory of complex spherical fuzzy sets (CSFSs) is a mixture of two theories, i.e., complex fuzzy sets (CFSs) and spherical fuzzy sets (SFSs), to cope with uncertain and unreliable information in realistic decision-making situations. CSFSs contain three grades in the form of polar coordinates, e.g., truth, abstinence, and falsity, belonging to a unit disc in a complex plane, with a condition that the sum of squares of the real part of the truth, abstinence, and falsity grades is not exceeded by a unit interval. In this paper, we first consider some properties and their operational laws of CSFSs. Additionally, based on CSFSs, the complex spherical fuzzy Bonferroni mean (CSFBM) and complex spherical fuzzy weighted Bonferroni mean (CSFWBM) operators are proposed. The special cases of the proposed operators are also discussed. A multi-attribute decision making (MADM) problem was chosen to be resolved based on the proposed CSFBM and CSFWBM operators. We then propose the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method based on CSFSs (CSFS-TOPSIS). An application example is given to delineate the proposed methods and a close examination is undertaken. The advantages and comparative analysis of the proposed approaches are also presented.

A New Method of Multi-Attribute Decision-Making Based on Grey Relational Analysis with Time Series

2013 ◽  
Vol 444-445 ◽  
pp. 666-670
Author(s):  
Yi Zhang
Keyword(s):  
Decision Making ◽  
Time Series ◽  
Grey Relational Analysis ◽  
Uncertain Information ◽  
Decision Method ◽  
Rational Decision Making ◽  
Relational Analysis ◽  
Multi Attribute Decision Making ◽  
Subjective Views ◽  
Grey Relational

For the multi-attribute decision making with time series, based on the comprehensive consideration of various indicators of quality and growth degree, with grey relational analysis on less data, uncertain information can be integrated comparison, so we put forward a new decision method considering the decision maker subjective views, and provide a scientific and rational decision-making method. By the example, that method is viable.

scholarly journals FINDING A PROMISING VENTURE CAPITAL PROJECT WITH TODIM UNDER PROBABILISTIC HESITANT FUZZY CIRCUMSTANCE

2018 ◽  
Vol 24 (5) ◽  
pp. 2026-2044 ◽  
Author(s):  
Weike Zhang ◽  
Jiang Du ◽  
Xiaoli Tian
Keyword(s):  
Decision Making ◽  
Group Decision ◽  
Venture Capitalists ◽  
Fuzzy Information ◽  
Investment Environment ◽  
Limited Ability ◽  
Risk Seeking ◽  
Decision Making Problem ◽  
Criteria Weights

Considering the risk aversion for gains and the risk seeking for losses of venture capitalists, the TODIM has been chosen as the decision-making method. Moreover, group decision is an available way to avoid the limited ability and knowledge etc. of venture capitalists. Simultaneously, venture capitalists may be hesitant among several assessed values with different probabilities to express their real perception because of the uncertain decision-making environment. However, the probabilistic hesitant fuzzy information can solve such problems effectively. Therefore, the TODIM has been extended to probabilistic hesitant fuzzy circumstance for the sake of settling the decision-making problem of venture capitalists in this paper. Moreover, due to the uncertain investment environment, the criteria weights are considered as probabilistic hesitant fuzzy information as well. Then, a case study has been used to verify the feasibility and validity of the proposed TODIM. Also, the TODIM with hesitant fuzzy information has been carried out to analysis the same case. From the comparative analysis, the superiority of the proposed TODIM in this paper has already appeared.

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