Pythagorean triangular fuzzy linguistic bonferroni mean operators and their application for multi-attribute decision making

2017 ◽  
Author(s):  
Na Jing ◽  
Sidong Xian ◽  
Yue Xiao
Keyword(s):  
Decision Making ◽  
Bonferroni Mean ◽  
Multi Attribute Decision Making ◽  
Fuzzy Linguistic

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.

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.

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.

scholarly journals A Novel Multi-Attribute Decision Making Method Based on The Double Hierarchy Hesitant Fuzzy Linguistic Generalized Power Aggregation Operator

Information ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 339 ◽  
Author(s):  
Liu ◽  
Zhao ◽  
Li ◽  
Wang ◽  
Wang
Keyword(s):  
Decision Making ◽  
Aggregation Operators ◽  
Linguistic Context ◽  
Practical Application ◽  
Linguistic Expression ◽  
Novel Approach ◽  
Linguistic Term ◽  
Multi Attribute Decision Making ◽  
Complex Decision ◽  
Fuzzy Linguistic

. A double hierarchy hesitant fuzzy linguistic term set (DHHFLT) is deemed as an effective and powerful linguistic expression which models complex linguistic decision information more accurately by using two different hierarchy linguistic term sets. The purpose of this paper is to propose a multi-attribute decision making method to tackle complex decision issues in which attribute values are represented as double hierarchy hesitant fuzzy linguistic numbers, and there are some extreme or unreasonable data in the attribute values. To do this, firstly, four double hierarchy hesitant fuzzy linguistic generalized power aggregation operators are introduced, including the double hierarchy hesitant fuzzy linguistic generalized power average (DHHFLGPA) operator, the double hierarchy hesitant fuzzy linguistic generalized power geometric (DHHFLGPG) operator, and their weighted forms. Thereafter, several favorable properties, as well as representative cases of the proposed operators, are investigated in detail. Moreover, by virtue of the proposed operators, a novel approach is developed for coping with multi-attribute decision making cases in the double hierarchy hesitant fuzzy linguistic context. Finally, an illustrated example is given to demonstrate the practical application of the presented approach, an availability verification is given to show its validity, and a comparative analysis is also conducted to highlight the advantages of the proposed approach.

scholarly journals A Novel Decision-Making Model with Pythagorean Fuzzy Linguistic Information Measures and Its Application to a Sustainable Blockchain Product Assessment Problem

2019 ◽  
Vol 11 (20) ◽  
pp. 5630 ◽  
Author(s):  
Feifei Jin ◽  
Lidan Pei ◽  
Huayou Chen ◽  
Reza Langari ◽  
Jinpei Liu
Keyword(s):  
Decision Making ◽  
Similarity Measure ◽  
Membership Degree ◽  
Linguistic Information ◽  
Information Measures ◽  
New Information ◽  
Multi Attribute Decision Making ◽  
Product Assessment ◽  
Decision Making Model ◽  
Fuzzy Linguistic

This study presents a novel multi-attribute decision-making (MADM) model on the basis of Pythagorean fuzzy linguistic information measures. To do so, we first present a new concept of Pythagorean fuzzy linguistic sets to describe fuzziness and inconsistent information, in which the Pythagorean fuzzy linguistic values (PFLVs) are represented by the linguistic membership degree and linguistic non-membership degree. Then, we introduce two axiomatic definitions of information measures for PFLVs, including Pythagorean fuzzy linguistic entropy and the Pythagorean fuzzy linguistic similarity measure, to measure the uncertainty degree of PFLVs and the similarity degree between among PFLVs. In addition, based on the logarithmic function, we construct two new information measure formulas and verify that they satisfy the axiomatic conditions of the Pythagorean fuzzy linguistic entropy and similarity measure, respectively. We further explore the relationship between the Pythagorean fuzzy linguistic entropy and similarity measure. Finally, we present a novel Pythagorean fuzzy linguistic MADM model with the Pythagorean fuzzy linguistic entropy and similarity measure. A numerical example of selecting the most desirable sustainable blockchain product is given, and a comparison with the existing approach was performed to validate the reliability of the developed decision-making model.

Evaluation of sustainable e-waste collection method for urban and rural region of India

2021 ◽  
pp. 0734242X2110185
Author(s):  
Shailender Singh ◽  
Mani Sankar Dasgupta ◽  
Srikanta Routroy
Keyword(s):  
Decision Making ◽  
Electronic Waste ◽  
Retail Store ◽  
Waste Collection ◽  
Collection Method ◽  
Evaluation Scheme ◽  
Take Back ◽  
Multi Attribute Decision Making ◽  
Decision Making Model ◽  
Fuzzy Linguistic

Electronic waste is one of the most challenging waste streams to manage. It has become a significant concern in developing countries due to the ever-increasing volume of generation coupled with deficient growth in collection and processing infrastructure. For the various stakeholders, it is of paramount importance to adopt a robust and sustainable collection method for hazard mitigation. The prevalent e-waste collection methods are categorized under four major heads, namely take-back, retail store, door-to-door and curbside collection. The e-waste collection problems are analysed from various perspective, based on literature that cited developing country-specific survey and data that includes India. Economic sustainability and potential risk are included as attributes in the evaluation scheme. We attempt to establish a decision-making model. Discussion with the field experts and decision-makers (DMs) provided the weights for various attributes and sub-attributes. A fuzzy linguistic scale is used to take care of ambiguity in DMs’ opinion. Fuzzy- Analytical Hierarchy Process (FAHP) is used to determine the importance of various attributes and sub-attributes, while Fuzzy-VlseKriterijumska Optimizacija I Kompromisno Resenje (FVIKOR) is used to determine the rank of the alternatives. Based on the analysis, ‘take-back collection’ and ‘retail store based collection’ are found the most suitable options for urban and rural regions respectively. The attributes, social awareness and economical sustainability are found to have the highest significance in both cases. Implementation of a collection method is an expensive activity, and the proposed Fuzzy-Multi Attribute Decision Making attempts to capture various attributes and their complex interplay to arrive at a decision on optimum e-waste collection option(s) in a specific locality.

AN APPROACH FOR COMBINING LINGUISTIC AND NUMERICAL INFORMATION BASED ON THE 2-TUPLE FUZZY LINGUISTIC REPRESENTATION MODEL IN DECISION-MAKING

2000 ◽  
Vol 08 (05) ◽  
pp. 539-562 ◽  
Author(s):  
F. HERRERA ◽  
L. MARTINEZ
Keyword(s):  
Decision Making ◽  
Linguistic Information ◽  
Loss Of Information ◽  
Linguistic Representation ◽  
Representation Model ◽  
Decision Making Problem ◽  
Linguistic Term ◽  
Multi Attribute Decision Making ◽  
Fuzzy Linguistic ◽  
Transformation Processes

In this paper we shall develop a procedure for combining numerical and linguistic information without loss of information in the transformation processes between numerical and linguistic information, taking as base for representing the information the 2-tuple fuzzy linguistic representation model. We shall analyze the conditions to impose the linguistic term set in order to ensure that the combination procedure does not produce any loss of information. Afterwards the aggregation process will be applied to a decision procedure over a multi-attribute decision-making problem dealing with numerical and linguistic information, that is, with qualitative and quantitative attributes.

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