scholarly journals Novel Distance Measure in Fuzzy TOPSIS to Improve Ranking Process: An Application to the Spanish Grocery Industry

2019 ◽  
Vol 53 (1/2019) ◽  
pp. 125-140
Author(s):  
REIG-MULLOR JAVIER ◽  
PLA-SANTAMARIA DAVID ◽  
GARCIA-BERNABEU ANA ◽  
SALAS-MOLINA FRANCISCO
Keyword(s):  
Distance Measure ◽  
Fuzzy Topsis ◽  
Grocery Industry

scholarly journals Extended Version of Linguistic Picture Fuzzy TOPSIS Method and Its Applications in Enterprise Resource Planning Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Shouzhen Zeng ◽  
Muhammad Qiyas ◽  
Muhammad Arif ◽  
Tariq Mahmood
Keyword(s):  
Enterprise Resource Planning ◽  
Fuzzy Numbers ◽  
Distance Measure ◽  
Hamming Distance ◽  
Resource Planning ◽  
Fuzzy Topsis ◽  
Extended Version ◽  
Topsis Method ◽  
Planning Systems ◽  
Enterprise Resource Planning Systems

The main objective of the proposed research in this paper is introducing an extended version of the linguistic picture fuzzy TOPSIS technique and then solving the problems in enterprise resource planning systems. In this article, we use the uncertain information in terms of linguistic picture fuzzy numbers; the decision maker provides membership, neutral, and nonmembership fuzzy linguistic terms to represent uncertain assessments information of alternatives in linguistic multicriteria decision making (LMCDMs). In order to introduce the extended version of TOPSIS method, we defined a new hamming distance measure between two linguistic picture fuzzy numbers. Further, we apply the proposed method to problem of enterprise resource planning systems and discuss numerical implementation of the proposed method of LMCDM.

Intuitionistic Fuzzy Distance-Based Intuitionistic Fuzzy TOPSIS Method and Application to MADM

2017 ◽  
pp. 72-96
Author(s):  
Jiangxia Nan ◽  
Ting Wang ◽  
Jingjing An
Keyword(s):  
Distance Measure ◽  
Fuzzy Topsis ◽  
Distance Measures ◽  
Ideal Solution ◽  
Intuitionistic Fuzzy Numbers ◽  
Metric Properties ◽  
Fuzzy Distance ◽  
Intuitionistic Fuzzy ◽  
Multi Attribute Decision Making ◽  
Negative Ideal Solution

In this paper, an intuitionistic fuzzy (IF) distance measure between two triangular intuitionistic fuzzy numbers (TIFNs) is developed. The metric properties of the proposed IF distance measures are also studied. Then, based on the IF distance, an extended TOPSIS is developed to solve multi-attribute decision making (MADM) problems with the ratings of alternatives on attributes of TIFNs. In this methodology, the IF distances between each alternative and the TIFN positive ideal-solution are calculated as well as the TIFN negative ideal-solution. Then the relative closeness degrees obtained of each alternative to the TIFN positive ideal solution are TIFNs. Based on the ranking methods of TIFNs the alternatives are ranked. A numerical example is examined to the validity and practicability of the method proposed in this paper.

scholarly journals Novel Distance Measure in Fuzzy TOPSIS for Supply Chain Strategy Based Supplier Selection

2016 ◽  
Vol 2016 ◽  
pp. 1-17 ◽  
Author(s):  
B. Pardha Saradhi ◽  
N. Ravi Shankar ◽  
Ch. Suryanarayana
Keyword(s):  
Supply Chain ◽  
Balanced Scorecard ◽  
Fuzzy Number ◽  
Supplier Selection ◽  
Distance Measure ◽  
Fuzzy Topsis ◽  
Research Area ◽  
Manufacturing Strategy ◽  
Supply Chain Strategy ◽  
Trapezoidal Fuzzy Number

In today’s highly competitive environment, organizations need to evaluate and select suppliers based on their manufacturing strategy. Identification of supply chain strategy of the organization, determination of decision criteria, and methods of supplier selection are appearing to be the most important components in research area in the field of supply chain management. In this paper, evaluation of suppliers is done based on the balanced scorecard framework using new distance measure in fuzzy TOPSIS by considering the supply chain strategy of the manufacturing organization. To take care of vagueness in decision making, trapezoidal fuzzy number is assumed for pairwise comparisons to determine relative weights of perspectives and criteria of supplier selection. Also, linguistic variables specified in terms of trapezoidal fuzzy number are considered for the payoff values of criteria of the suppliers. These fuzzy numbers satisfied the Jensen based inequality. A detailed application of the proposed methodology is illustrated.

scholarly journals A New Approach to Fuzzy TOPSIS Method Based on Entropy Measure under Spherical Fuzzy Information

Entropy ◽  
2019 ◽  
Vol 21 (12) ◽  
pp. 1231 ◽  
Author(s):  
Omar Barukab ◽  
Saleem Abdullah ◽  
Shahzaib Ashraf ◽  
Muhammad Arif ◽  
Sher Afzal Khan
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Distance Measure ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Entropy Measure ◽  
Fuzzy Decision ◽  
Fuzzy Information ◽  
Comparative Results ◽  
Robot Selection

Spherical fuzzy set (SFS) is one of the most important and extensive concept to accommodate more uncertainties than existing fuzzy set structures. In this article, we will describe a novel enhanced TOPSIS-based procedure for tackling multi attribute group decision making (MAGDM) issues under spherical fuzzy setting, in which the weights of both decision-makers (DMs) and criteria are totally unknown. First, we study the notion of SFSs, the score and accuracy functions of SFSs and their basic operating laws. In addition, defined the generalized distance measure for SFSs based on spherical fuzzy entropy measure to compute the unknown weights information. Secondly, the spherical fuzzy information-based decision-making technique for MAGDM is presented. Lastly, an illustrative example is delivered with robot selection to reveal the efficiency of the proposed spherical fuzzy decision support approach, along with the discussion of comparative results, to prove that their results are feasible and credible.

scholarly journals Entropy Based Pythagorean Probabilistic Hesitant Fuzzy Decision Making Technique and Its Application for Fog-Haze Factor Assessment Problem

Entropy ◽  
2020 ◽  
Vol 22 (3) ◽  
pp. 318 ◽  
Author(s):  
Bushra Batool ◽  
Mumtaz Ahmad ◽  
Saleem Abdullah ◽  
Shahzaib Ashraf ◽  
Ronnason Chinram
Keyword(s):  
Influence Factor ◽  
Distance Measure ◽  
Real Life ◽  
Detailed Comparison ◽  
Fuzzy Topsis ◽  
Hesitant Fuzzy Set ◽  
Entropy Measure ◽  
Fuzzy Decision Making ◽  
Fuzzy Evaluation ◽  
Life Problems

The Pythagorean probabilistic hesitant fuzzy set (PyPHFS) is an effective, generalized and powerful tool for expressing fuzzy information. It can cover more complex and more hesitant fuzzy evaluation information. Therefore, based on the advantages of PyPHFSs, this paper presents a new extended fuzzy TOPSIS method for dealing with uncertainty in the form of PyPHFS in real life problems. The paper is divided into three main parts. Firstly, the novel Pythagorean probabilistic hesitant fuzzy entropy measure is established using generalized distance measure under PyPHFS information to find out the unknown weights information of the attributes. The second part consists of the algorithm sets of the TOPSIS technique under PyPHFS environment, where the weights of criteria are completely unknown. Finally, in order to verify the efficiency and superiority of the proposed method, this paper applies some practical examples of the selection of the most critical fog-haze influence factor and makes a detailed comparison with other existing methods.

scholarly journals Decision Support Methodology Based on Covering-Based Interval-Valued Pythagorean Fuzzy Rough Set Model and Its Application to Hospital Open-Source EHRs System Selection

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Fang Liu ◽  
Ju Wu ◽  
Lianming Mou ◽  
Yi Liu
Keyword(s):  
Rough Set ◽  
Distance Measure ◽  
Fuzzy Topsis ◽  
Fuzzy Information ◽  
Pythagorean Fuzzy Set ◽  
Fuzzy Rough Set ◽  
New Approach ◽  
System Selection ◽  
Pythagorean Fuzzy Numbers ◽  
Interval Valued

The target of current work is to propose a new approach to deal with multiattribute decision-making (MADM) problems with interval-valued Pythagorean fuzzy set (IVPFS) based on the concepts of covering-based rough set (CRS) and TOPSIS and give its application in MADM problems. To begin with, we integrate the fuzzy rough set (FRS), IVPFS and CRS and define the covering-based interval-valued Pythagorean fuzzy rough set (CIVPFRS). Firstly, the relative notions of the CIVPFRS model are introduced. In addition, the distance measure of interval-valued Pythagorean fuzzy numbers (IVPFNs) is defined; based on the proposed distance, the rough and precision degrees of CIVPFRS are discussed. Thirdly, on the basis of the theoretical analysis for CIVPFRS models, an interval-valued Pythagorean fuzzy TOPSIS method is designed to deal with the MADM problems with interval-valued Pythagorean fuzzy information (IVPFI). Last of all, the validity and merits of the proposed approach are illustrated by an example, and the sensitivity analysis of the parameters and the comparison with the existing related methods are carried out.β

Feature selection of the armature winding broken coils in synchronous motor using genetic algorithm and mahalanobis distance

2012 ◽  
Vol 57 (3) ◽  
pp. 829-835 ◽  
Author(s):  
Z. Głowacz ◽  
J. Kozik
Keyword(s):  
Genetic Algorithm ◽  
Feature Selection ◽  
Mahalanobis Distance ◽  
Distance Measure ◽  
Synchronous Motor ◽  
Medical Diagnostics ◽  
Motor Current ◽  
Feature Spaces ◽  
Multidimensional Feature Spaces ◽  
Selection Of

The paper describes a procedure for automatic selection of symptoms accompanying the break in the synchronous motor armature winding coils. This procedure, called the feature selection, leads to choosing from a full set of features describing the problem, such a subset that would allow the best distinguishing between healthy and damaged states. As the features the spectra components amplitudes of the motor current signals were used. The full spectra of current signals are considered as the multidimensional feature spaces and their subspaces are tested. Particular subspaces are chosen with the aid of genetic algorithm and their goodness is tested using Mahalanobis distance measure. The algorithm searches for such a subspaces for which this distance is the greatest. The algorithm is very efficient and, as it was confirmed by research, leads to good results. The proposed technique is successfully applied in many other fields of science and technology, including medical diagnostics.

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