scholarly journals Interval Valued T-Spherical Fuzzy Soft Average Aggregation Operators and Their Applications in Multiple-Criteria Decision Making

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 829
Author(s):  
Tahir Mahmood ◽  
Jabbar Ahmmad ◽  
Zeeshan Ali ◽  
Dragan Pamucar ◽  
Dragan Marinkovic
Keyword(s):  
Decision Making ◽  
Asymmetric Information ◽  
Fuzzy Set ◽  
Multiple Criteria Decision Making ◽  
Weighted Average ◽  
Aggregation Operators ◽  
Multiple Criteria ◽  
Soft Set ◽  
Operator Interval ◽  
Interval Valued

This paper deals with uncertainty, asymmetric information, and risk modelling in a complex power system. The uncertainty is managed by using probability and decision theory methods. Multiple-criteria decision making (MCDM) is a very effective and well-known tool to investigate fuzzy information more effectively. However, the selection of houses cannot be done by utilizing symmetry information, because enterprises do not have complete information, so asymmetric information should be used when selecting enterprises. In this paper, the notion of soft set (SftS) and interval-valued T-spherical fuzzy set (IVT-SFS) are combined to produce a new and more effective notion called interval-valued T-spherical fuzzy soft set (IVT-SFSftS). It is a more general concept and provides more space and options to decision makers (DMs) for making their decision in the field of fuzzy set theory. Moreover, some average aggregation operators like interval-valued T-spherical fuzzy soft weighted average (IVT-SFSftWA) operator, interval-valued T-spherical fuzzy soft ordered weighted average (IVT-SFSftOWA) operator, and interval-valued T-spherical fuzzy soft hybrid average (IVT-SFSftHA) operators are explored. Furthermore, the properties of these operators are discussed in detail. An algorithm is developed and an application example is proposed to show the validity of the present work. This manuscript shows how to make a decision when there is asymmetric information about an enterprise. Further, in comparative analysis, the established work is compared with another existing method to show the advantages of the present work.

scholarly journals q-Rung Orthopair Fuzzy N-Soft Aggregation Operators and Corresponding Applications to Multiple-Attribute Group Decision Making

2021 ◽  
Author(s):  
Haidong Zhang ◽  
TaiBen Nan ◽  
Yanping He
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Set ◽  
Group Decision ◽  
Weighted Average ◽  
Aggregation Operators ◽  
Soft Set ◽  
Multiple Attribute

Abstract In this paper, by integrating the q-rung orthopair fuzzy set (q-ROFS) with the N-soft set (NSS), we first propose a q-rung orthopair fuzzy N-soft set (q-ROFNSS). Based on the q-ROFNSS, then we explore the q-rung orthopair fuzzy N-soft weighted average (q-ROFNSWA) operator and q-rung orthopair fuzzy N-soft weighted geometric (q-ROFNSWG) operator, and investigate some properties of the q-ROFNSWG operator and q-ROFNSWG operator including idempotency, monotonicity and boundedness. Finally, two kinds of multiple-attribute group decision making (MAGDM) methods based on q-rung orthopair fuzzy N-soft aggregation operators are established. In addition, a practical example is provided to illustrate the effectiveness and correctness of the new decision-making approaches. Through comparison with existing methods, the advantages of our method are elaborated.

A Hybrid Method for Pythagorean Fuzzy Multiple-Criteria Decision Making

2016 ◽  
Vol 15 (02) ◽  
pp. 403-422 ◽  
Author(s):  
Shouzhen Zeng ◽  
Jianping Chen ◽  
Xingsen Li
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Intuitionistic Fuzzy Set ◽  
Multiple Criteria Decision Making ◽  
Weighted Average ◽  
Multiple Criteria ◽  
Distance Measures ◽  
Weighted Averaging ◽  
Ordered Weighted Averaging ◽  
Special Cases

As a generalization of intuitionistic fuzzy set, the Pythagorean fuzzy set is interesting and very useful in modeling uncertain information in real-world decision-making problems. In this paper, we develop a new method for Pythagorean fuzzy multiple-criteria decision-making (MCDM) problems with aggregation operators and distance measures. First, we present the Pythagorean fuzzy ordered weighted averaging weighted average distance (PFOWAWAD) operator. The main advantage of the PFOWAWAD operator is that it uses distance measures in a unified framework between the ordered weighted averaging (OWA) operator and weighted average (WA) that considers the degree of importance of each concept in the aggregation. Some of its main properties and special cases are studied. Then, based on the proposed operator, a hybrid TOPSIS method, called PFOWAWAD-TOPSIS is introduced for Pythagorean fuzzy MCDM problem. Finally, a numerical example is provided to illustrate the practicality and feasibility of the developed method.

scholarly journals Picture Hesitant Fuzzy Set and Its Application to Multiple Criteria Decision-Making

Symmetry ◽  
2018 ◽  
Vol 10 (7) ◽  
pp. 295 ◽  
Author(s):  
Rui Wang ◽  
Yanlai Li
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Real Life ◽  
Multiple Criteria Decision Making ◽  
Service Selection ◽  
Aggregation Operators ◽  
Multiple Criteria ◽  
Hesitant Fuzzy Set ◽  
Web Service Selection ◽  
Picture Fuzzy Set

To address the complex multiple criteria decision-making (MCDM) problems in practice, this article proposes the picture hesitant fuzzy set (PHFS) theory based on the picture fuzzy set and the hesitant fuzzy set. First, the concept of PHFS is put forward, and its operations are presented, simultaneously. Second, the generalized picture hesitant fuzzy weighted aggregation operators are developed, and some theorems and reduced operators of them are discussed. Third, the generalized picture hesitant fuzzy prioritized weighted aggregation operators are put forward to solve the MCDM problems that the related criteria are at different priorities. Fourth, two novel MCDM methods combined with the proposed operators are constructed to determine the best alternative in real life. Finally, two numerical examples and an application of web service selection are investigated to illustrate the effectiveness of the proposed methods. The sensitivity analysis shows that the different values of the parameter λ affect the ranking of alternatives, and the proposed operators are compared with several existing MCDM methods to illustrate their advantages.

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.

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 Generalised Interval-Valued Fuzzy Soft Set

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Shawkat Alkhazaleh ◽  
Abdul Razak Salleh
Keyword(s):  
Decision Making ◽  
Similarity Measure ◽  
Fuzzy Set ◽  
Medical Diagnosis ◽  
Soft Set ◽  
Fuzzy Soft Set ◽  
Soft Sets ◽  
Decision Making Problem ◽  
Fuzzy Soft Sets ◽  
Interval Valued

We introduce the concept of generalised interval-valued fuzzy soft set and its operations and study some of their properties. We give applications of this theory in solving a decision making problem. We also introduce a similarity measure of two generalised interval-valued fuzzy soft sets and discuss its application in a medical diagnosis problem: fuzzy set; soft set; fuzzy soft set; generalised fuzzy soft set; generalised interval-valued fuzzy soft set; interval-valued fuzzy set; interval-valued fuzzy soft set.

scholarly journals A Q-RUNG ORTHOPAIR FUZZY GLDS METHOD FOR INVESTMENT EVALUATION OF BE ANGEL CAPITAL IN CHINA

2020 ◽  
Vol 26 (1) ◽  
pp. 103-134 ◽  
Author(s):  
Huchang Liao ◽  
Hongrun Zhang ◽  
Cheng Zhang ◽  
Xingli Wu ◽  
Abbas Mardani ◽  
...  
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Distance Measure ◽  
Intuitionistic Fuzzy Set ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Investment Evaluation ◽  
Dominance Score ◽  
Do So

As a generalized form of both intuitionistic fuzzy set and Pythagorean fuzzy sets, the q-rung orthopair fuzzy set (q-ROFS) has strong ability to handle uncertain or imprecision decisionmaking problems. This paper aims to introduce a new multiple criteria decision making method based on the original gain and lost dominance score (GLDS) method for investment evaluation. To do so, we first propose a new distance measure of q-rung orthopair fuzzy numbers (q-ROFNs), which takes into account the hesitancy degree of q-ROFNs. Subsequently, two methods are developed to determine the weights of DMs and criteria, respectively. Next, the original GLDS method is improved from the aspects of dominance flows and order scores of alternatives to address the multiple criteria decision making problems with q-ROFS information. Finally, a case study concerning the investment evaluation of the BE angle capital is given to illustrate the applicability and superiority of the proposed method.

Comparative analysis of evolutionary algorithms for multiple criteria decision making with interval-valued belief distributions

2020 ◽  
Vol 14 (3) ◽  
pp. 373-391
Author(s):  
Guangyan Lu ◽  
Wenjun Chang
Keyword(s):  
Decision Making ◽  
Particle Swarm Optimization ◽  
Comparative Analysis ◽  
Evolutionary Algorithms ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Swarm Optimization ◽  
Interval Valued

In multiple criteria decision making (MCDM) with interval-valued belief distributions (IVBDs), individual IVBDs on multiple criteria are combined explicitly or implicitly to generate the expected utilities of alternatives, which can be used to make decisions with the aid of decision rules. To analyze an MCDM problem with a large number of criteria and grades used to profile IVBDs, effective algorithms are required to find the solutions to the optimization models within a large feasible region. An important issue is to identify an algorithm suitable for finding accurate solutions within a limited or acceptable time. To address this issue, four representative evolutionary algorithms, including genetic algorithm, differential evolution algorithm, particle swarm optimization algorithm, and gravitational search algorithm, are selected to combine individual IVBDs of alternatives and generate the minimum and maximum expected utilities of alternatives. By performing experiments with different numbers of criteria and grades, a comparative analysis of the four algorithms is provided with the aid of two indicators: accuracy and efficiency. Experimental results indicate that particle swarm optimization algorithm is the best among the four algorithms for combining individual IVBDs and generating the minimum and maximum expected utilities of alternatives.

Sign in / Sign up

Export Citation Format

Share Document