scholarly journals A simple modification to the EDAS method for two exceptional cases

2021 ◽  
Author(s):  
Mehdi Keshavarz-Ghorabaee
Keyword(s):  
Decision Making ◽  
Real World ◽  
Science And Technology ◽  
Engineering Science ◽  
Multi Criteria Decision Making ◽  
Simple Modification ◽  
Methods And Techniques ◽  
Mcdm Method ◽  
Real World Problems

Multi-criteria decision-making (MCDM) methods and techniques have been applied to many real-world problems in different fields of engineering science and technology. The evaluation based on distance from average solution (EDAS) method is a new and efficient MCDM method. The aim of this study is to propose a modification to address two exceptional cases in which the EDAS method fails to solve an MCDM problem.

scholarly journals Extended EDAS Method for Fuzzy Multi-criteria Decision-making: An Application to Supplier Selection

2016 ◽  
Vol 11 (3) ◽  
pp. 358 ◽  
Author(s):  
Mehdi Keshavarz Ghorabaee ◽  
Edmundas Kazimieras Zavadskas ◽  
Maghsoud Amiri ◽  
Zenonas Turskis
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Real World ◽  
Supplier Selection ◽  
Multi Criteria Decision Making ◽  
Fuzzy Environment ◽  
Methods And Techniques ◽  
The Stability ◽  
Real World Problems

In the real-world problems, we are likely confronted with some alternatives that eed to be evaluated with respect to multiple conflicting criteria. Multi-criteria ecision-making (MCDM) refers to making decisions in such a situation. There are any methods and techniques available for solving MCDM problems. The evaluation ased on distance from average solution (EDAS) method is an efficient multi-criteria ecision-making method. Because the uncertainty is usually an inevitable part of he MCDM problems, fuzzy MCDM methods can be very useful for dealing with the eal-world decision-making problems. In this study, we extend the EDAS method o handle the MCDM problems in the fuzzy environment. A case study of supplier election is used to show the procedure of the proposed method and applicability of t. Also, we perform a sensitivity analysis by using simulated weights for criteria to xamine the stability and validity of the results of the proposed method. The results f this study show that the extended fuzzy EDAS method is efficient and has good tability for solving MCDM problems.

scholarly journals Application of Improved Best Worst Method (BWM) in Real-World Problems

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1342 ◽  
Author(s):  
Dragan Pamučar ◽  
Fatih Ecer ◽  
Goran Cirovic ◽  
Melfi A. Arlasheedi
Keyword(s):  
Decision Making ◽  
Renewable Energy ◽  
Real World ◽  
Evaluation Criteria ◽  
Decision Makers ◽  
Multi Criteria Decision Making ◽  
Weight Coefficients ◽  
Best Worst Method ◽  
Real World Problems

The Best Worst Method (BWM) represents a powerful tool for multi-criteria decision-making and defining criteria weight coefficients. However, while solving real-world problems, there are specific multi-criteria problems where several criteria exert the same influence on decision-making. In such situations, the traditional postulates of the BWM imply the defining of one best criterion and one worst criterion from within a set of observed criteria. In this paper, an improvement of the traditional BWM that eliminates this problem is presented. The improved BWM (BWM-I) offers the possibility for decision-makers to express their preferences even in cases where there is more than one best and worst criterion. The development enables the following: (1) the BWM-I enables us to express experts’ preferences irrespective of the number of the best/worst criteria in a set of evaluation criteria; (2) the application of the BWM-I reduces the possibility of making a mistake while comparing pairs of criteria, which increases the reliability of the results; and (3) the BWM-I is characterized by its flexibility, which is expressed through the possibility of the realistic processing of experts’ preferences irrespective of the number of the criteria that have the same significance and the possibility of the transformation of the BWM-I into the traditional BWM (should there be a unique best/worst criterion). To present the applicability of the BWM-I, it was applied to defining the weight coefficients of the criteria in the field of renewable energy and their ranking.

An algebraic approach to N-soft sets with application in decision-making using TOPSIS

2021 ◽  
pp. 1-21
Author(s):  
Muhammad Shabir ◽  
Rimsha Mushtaq ◽  
Munazza Naz
Keyword(s):  
Decision Making ◽  
Mathematical Models ◽  
Real World ◽  
Algebraic Approach ◽  
Multi Criteria Decision Making ◽  
Commutative Monoids ◽  
Soft Sets ◽  
Algebraic Properties ◽  
Different Types ◽  
Selection Of

In this paper, we focus on two main objectives. Firstly, we define some binary and unary operations on N-soft sets and study their algebraic properties. In unary operations, three different types of complements are studied. We prove De Morgan’s laws concerning top complements and for bottom complements for N-soft sets where N is fixed and provide a counterexample to show that De Morgan’s laws do not hold if we take different N. Then, we study different collections of N-soft sets which become idempotent commutative monoids and consequently show, that, these monoids give rise to hemirings of N-soft sets. Some of these hemirings are turned out as lattices. Finally, we show that the collection of all N-soft sets with full parameter set E and collection of all N-soft sets with parameter subset A are Stone Algebras. The second objective is to integrate the well-known technique of TOPSIS and N-soft set-based mathematical models from the real world. We discuss a hybrid model of multi-criteria decision-making combining the TOPSIS and N-soft sets and present an algorithm with implementation on the selection of the best model of laptop.

scholarly journals Complex T-spherical fuzzy Dombi aggregation operators and their applications in multiple-criteria decision-making

2021 ◽  
Author(s):  
Faruk Karaaslan ◽  
Mohammed Allaw Dawood Dawood
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Fuzzy Set ◽  
Multiple Criteria Decision Making ◽  
Aggregation Operators ◽  
Multi Criteria Decision Making ◽  
Two Dimensional ◽  
Weighted Arithmetic ◽  
Mcdm Method ◽  
Dombi Operations

AbstractComplex fuzzy (CF) sets (CFSs) have a significant role in modelling the problems involving two-dimensional information. Recently, the extensions of CFSs have gained the attention of researchers studying decision-making methods. The complex T-spherical fuzzy set (CTSFS) is an extension of the CFSs introduced in the last times. In this paper, we introduce the Dombi operations on CTSFSs. Based on Dombi operators, we define some aggregation operators, including complex T-spherical Dombi fuzzy weighted arithmetic averaging (CTSDFWAA) operator, complex T-spherical Dombi fuzzy weighted geometric averaging (CTSDFWGA) operator, complex T-spherical Dombi fuzzy ordered weighted arithmetic averaging (CTSDFOWAA) operator, complex T-spherical Dombi fuzzy ordered weighted geometric averaging (CTSDFOWGA) operator, and we obtain some of their properties. In addition, we develop a multi-criteria decision-making (MCDM) method under the CTSF environment and present an algorithm for the proposed method. To show the process of the proposed method, we present an example related to diagnosing the COVID-19. Besides this, we present a sensitivity analysis to reveal the advantages and restrictions of our method.

scholarly journals Selection Of Cutting Inserts For Aluminum Alloys Machining By Using MCDM Method

2015 ◽  
Vol 66 (1) ◽  
pp. 98-101 ◽  
Author(s):  
Miloš Madić ◽  
Miroslav Radovanović ◽  
Dušan Petković ◽  
Bogdan Nedić
Keyword(s):  
Decision Making ◽  
Aluminum Alloys ◽  
Cutting Tool ◽  
Cutting Tools ◽  
Multi Criteria Decision Making ◽  
Complex Task ◽  
Cutting Inserts ◽  
Mcdm Method ◽  
Product Assessment ◽  
Selection Of

Abstract Machining of aluminum and its alloys requires the use of cutting tools with special geometry and material. Since there exists a number of cutting tools for aluminum machining, each with unique characteristics, selection of the most appropriate cutting tool for a given application is very complex task which can be viewed as a multi-criteria decision making (MCDM) problem. This paper is focused on multi-criteria analysis of VCGT cutting inserts for aluminum alloys turning by applying recently developed MCDM method, i.e. weighted aggregated sum product assessment (WASPAS) method. The MCDM model was defined using the available catalogue data from cutting tool manufacturers.

A GMCDM approach with linguistic Z-numbers based on TOPSIS and Choquet integral considering risk preference

2020 ◽  
Vol 39 (3) ◽  
pp. 4285-4298
Author(s):  
Ran Tao ◽  
Fuyuan Xiao
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Choquet Integral ◽  
Risk Preference ◽  
Decision Makers ◽  
Multi Criteria Decision Making ◽  
Uncertain Information ◽  
Human Knowledge ◽  
Mcdm Method ◽  
Evaluation Information

Group multi-criteria decision-making (GMCDM) is an important part of decision theory, which is aimed to assess alternatives according to multiple criteria by collecting the wisdom of experts. However, in the process of evaluating, because of the limitation of human knowledge and the complexity of problems, an efficient GMCDM approach under uncertain environment still need to be further explored. Thus, in this paper, a novel GMCDM approach with linguistic Z-numbers based on TOPSIS and Choquet integral is proposed. Firstly, since linguistic Z-numbers performs better in coping with uncertain information, it is used to express the evaluation information. Secondly, TOPSIS, one of the most useful and systematic multi-criteria decision-making (MCDM) method, is adopted as the framework of the proposed approach. Thirdly, frequently it exists interaction between criteria, so Choquet integral is introduced to capture this kind of influence. What’s more, viewing that decision makers (DMs) show different preferences for uncertainty, the risk preference is regarded as a vital parameter when calculating the score of linguistic Z-numbers. An application in supplier selection is illustrated to demonstrate the effectiveness of the proposed approach. Finally, a further comparison and discussion of the proposed GMCDM method is given.

scholarly journals Eliminating Rank Reversal Problem Using a New Multi-Attribute Model—The RAFSI Method

Mathematics ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 1015 ◽  
Author(s):  
Mališa Žižović ◽  
Dragan Pamučar ◽  
Miloljub Albijanić ◽  
Prasenjit Chatterjee ◽  
Ivan Pribićević
Keyword(s):  
Decision Making ◽  
Real World ◽  
Mathematical Formulation ◽  
Simple Algorithm ◽  
Data Normalization ◽  
Reversal Problem ◽  
Rank Reversal ◽  
Multi Attribute Decision Making ◽  
Attribute Model ◽  
Real World Problems

Multi-attribute decision-making (MADM) methods represent reliable ways to solve real-world problems for various applications by providing rational and logical solutions. In reaching such a goal, it is expected that MADM methods would eliminate inconsistencies like rank reversal issues in a given solution. In this paper, an endeavor is taken to put forward a new MADM method, called RAFSI (Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval), which successfully eliminates the rank reversal problem. The developed RAFSI method has three major advantages that recommend it for further use: (i) its simple algorithm helps in solving complex real-world problems, (ii) RAFSI method has a new approach for data normalization, which transfers data from the starting decision-making matrix into any interval, suitable for making rational decisions, (iii) mathematical formulation of RAFSI method eliminates the rank reversal problem, which is one of the most significant shortcomings of existing MADM methods. A real-time case study that shows the advantages of RAFSI method is presented. Additional comprehensive analysis, including a comparison with other three traditional MADM methods that use different ways for data normalization and testing the resistance of RAFSI method and other MADM methods to rank the reversal problem, is also carried out.

Adoption of Online Marketing for Service SMEs with Multi-Criteria Decision-Making Approach

2020 ◽  
pp. 356-374
Author(s):  
Lanndon Ocampo ◽  
Rosalin Merry Berdin Alarde ◽  
Dennis Anthony Kilongkilong ◽  
Antonio Esmero
Keyword(s):  
Decision Making ◽  
Small And Medium Enterprises ◽  
Analytic Network Process ◽  
Global Market ◽  
Service Industries ◽  
Online Marketing ◽  
Multi Criteria Decision Making ◽  
Network Process ◽  
Mcdm Method ◽  
Medium Enterprises

This chapter attempts to fill in the gap of evaluating the viability of adopting online marketing for small and medium enterprises (SMEs) in service industries. As SMEs are generally characterized by shortage of resources, the use of online marketing strategies is apparently difficult. However, the current landscape of competition among SMEs in a global market economy prompts the necessity of adopting online marketing. With these, the decision-making process of SMEs in this area becomes complex and the decisions must integrate complex and interrelating criteria and constructs in order to provide a more holistic solution. Thus, this work adopts a multi-criteria decision-making (MCDM) method particularly the analytic network process (ANP) in order to evaluate the practicability of using online marketing for service SMEs. It becomes highly relevant as it provides significant insights to decision-makers in SMEs regarding the use of online marketing strategy. The contribution of this chapter lies in the application of MCDM in evaluating viability of online marketing in service SMEs.

scholarly journals Multi-Criteria Decision Making Method with Belief Preference Relations

2014 ◽  
Vol 22 (04) ◽  
pp. 573-590 ◽  
Author(s):  
Amel Ennaceur ◽  
Zied Elouedi ◽  
Eric Lefèvre
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Belief Function ◽  
Multi Criteria Decision Making ◽  
Preference Assessments ◽  
Preference Relations ◽  
Expert Opinions ◽  
Expert Assessments ◽  
Mcdm Method ◽  
Modeling Expert

In modeling Multi-Criteria Decision Making (MCDM) problem, we usually assume that the decision maker is able to elicitate his preferences with precision and without difficulty. However, in many situations, the expert is unable to provide his assessment with certainty or he is unwilling to quantify his preferences. To deal with such situations, a new MCDM model under uncertainty is introduced. In fact, we focus here on the problem of modeling expert opinions despite the presence of incompleteness and uncertainty in their preference assessments. Besides, our proposed solution suggests to model these preferences qualitatively rather than exact numbers. Therefore, we propose to incorporate belief preference relations into a MCDM method. The expert assessments are then formulated as a belief function problem since this theory is considered as a useful tool to model expert judgments.

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