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.

Dynamic Multi-Attribute Decision Making Model with the Area Closeness Degree

2013 ◽  
Vol 321-324 ◽  
pp. 2557-2560
Author(s):  
Xi Juan Lou
Keyword(s):  
Decision Making ◽  
Ideal Solution ◽  
Raw Data ◽  
New Information ◽  
Multi Attribute Decision Making ◽  
Decision Making Model

The aim of this paper is to explore dynamic multi-attribute decision making (DMADM) problems in which the decision making information of alternatives is collected at different stages. Firstly, the area closeness degree is applied in normalizing the raw data. Secondly, the weights of different stages are determined by according to the principle of new information priority. The technique for preference by similarity to ideal solution (TOPSIS) is improved to aggregate the information from different stages. Finally, the example is illustrated to demonstrate the practicality and effectiveness of the proposed methods.

A Novel Linguistic Group Decision-Making Model Based on Extended Hesitant Fuzzy Linguistic Term Sets

2015 ◽  
Vol 23 (03) ◽  
pp. 379-398 ◽  
Author(s):  
Cuiping Wei ◽  
Na Zhao ◽  
Xijin Tang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Distance Measures ◽  
Linguistic Terms ◽  
Linguistic Information ◽  
Linguistic Group ◽  
Linguistic Term ◽  
Decision Making Model ◽  
Fuzzy Linguistic

Hesitant fuzzy linguistic term set (HFLTS) is a set with ordered consecutive linguistic terms, and is very useful in addressing the situations where people are hesitant in providing their linguistic assessments. Wang [H. Wang, Extended hesitant fuzzy linguistic term sets and their aggregation in group decision making, International Journal of Computational Intelligence Systems 8(1) (2015) 14–33.] removed the consecutive condition to introduce the notion of extended HFLTS (EHFLTS). The generalized form has wider applications in linguistic group decision-making. By introducing distance measures for EHFLTSs, in this paper we develop a novel multi-criteria group decision making model to deal with hesitant fuzzy linguistic information. The model collects group linguistic information by using EHFLTSs and avoids the possible loss of information. Moreover, it can assess the importance weights of criteria according to their subjective and objective information and rank alternatives based on the rationale of TOPSIS. In order to illustrate the applicability of the proposed algorithm, two examples are given and comparisons are made with the other existing methods.

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.

An algorithmic-based multi-attribute decision making model under intuitionistic fuzzy environment

2021 ◽  
pp. 1-15
Author(s):  
Eshika Aggarwal ◽  
B.K. Mohanty
Keyword(s):  
Decision Making ◽  
Confidence Level ◽  
Decision Aid ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Multi Attribute Decision Making ◽  
Product Assessment ◽  
Decision Making Model ◽  
Product Rating ◽  
Interval Valued

An outranking procedure for Multi-Attribute Decision-Making (MADM) problems is introduced in our work that acts as a decision-aid in recommending the products to the buyers. The buyer’s product assessment is taken as Interval-Valued Intuitionistic Fuzzy Sets (IVIFS) in each attribute. The confidence level that is implicit in the buyer’s product rating is explicated in the proposed work using fuzzy entropy. As the confidence level of the buyer on the product assessment is for both satisfaction and reluctance, it is suitably distributed in membership and non-membership parts of IVIFS. Our work generates a dominance matrix that represents partial or full dominance of one product over another after scoring the products that are unified with buyer’s confidence. The proposed work suggests the product ranking after ascertaining the buyer’s flexibility. An algorithm is written in our work to validate the procedure developed. We have compared our work with other similar works to highlight the benefits of the proposed work. A numerical example is illustrated to highlight the procedure developed.

Multi-Attribute Decision-Making Model by Applying Grey Numbers

Informatica ◽  
2009 ◽  
Vol 20 (2) ◽  
pp. 305-320 ◽  
Author(s):  
Edmundas Kazimieras Zavadskas ◽  
Arturas Kaklauskas ◽  
Zenonas Turskis ◽  
Jolanta Tamošaitienė
Keyword(s):  
Decision Making ◽  
Multi Attribute Decision Making ◽  
Decision Making Model

scholarly journals Approach to Multi-Attribute Decision-Making Methods for Performance Evaluation Process Using Interval-Valued T-Spherical Fuzzy Hamacher Aggregation Information

Axioms ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 145
Author(s):  
Yun Jin ◽  
Zareena Kousar ◽  
Kifayat Ullah ◽  
Tahir Mahmood ◽  
Nimet Yapici Pehlivan ◽  
...  
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Evaluation Process ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Membership Degree ◽  
Operational Laws ◽  
Multi Attribute Decision Making ◽  
Interval Valued ◽  
Do So

Interval-valued T-spherical fuzzy set (IVTSFS) handles uncertain and vague information by discussing their membership degree (MD), abstinence degree (AD), non-membership degree (NMD), and refusal degree (RD). MD, AD, NMD, and RD are defined in terms of closed subintervals of that reduce information loss compared to the T-spherical fuzzy set (TSFS), which takes crisp values from intervals; hence, some information may be lost. The purpose of this manuscript is to develop some Hamacher aggregation operators (HAOs) in the environment of IVTSFSs. To do so, some Hamacher operational laws based on Hamacher t-norms (HTNs) and Hamacher t-conorms (HTCNs) are introduced. Using Hamacher operational laws, we develop some aggregation operators (AOs), including an interval-valued T-spherical fuzzy Hamacher (IVTSFH) weighted averaging (IVTSFHWA) operator, an IVTSFH-ordered weighted averaging (IVTSFHOWA) operator, an IVTSFH hybrid averaging (IVTSFHHA) operator, an IVTSFH-weighted geometric (IVTSFHWG) operator, an IVTSFH-ordered weighted geometric (IVTSFHOWG) operator, and an IVTSFH hybrid geometric (IVTSFHHG) operator. The validation of the newly developed HAOs is investigated, and their basic properties are examined. In view of some restrictions, the generalization and proposed HAOs are shown, and a multi-attribute decision-making (MADM) procedure is explored based on the HAOs, which are further exemplified. Finally, a comparative analysis of the proposed work is also discussed with previous literature to show the superiority of our work.

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