scholarly journals Novel Approach for Third-Party Reverse Logistic Provider Selection Process under Linear Diophantine Fuzzy Prioritized Aggregation Operators

Symmetry ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1152
Author(s):  
Muhammad Riaz ◽  
Hafiz Muhammad Athar Farid ◽  
Muhammad Aslam ◽  
Dragan Pamucar ◽  
Darko Bozanić
Keyword(s):  
Selection Process ◽  
Real Life ◽  
Weighted Average ◽  
Primary Objective ◽  
Aggregation Operators ◽  
Third Party ◽  
Optimal Decision ◽  
Life Problems ◽  
Reverse Logistic ◽  
Prioritized Aggregation Operators

Aggregation operators are fundamental concept for information fusion in real-life problems. Many researchers developed aggregation operators for multi-criteria decision-making (MCDM) under uncertainty. Unfortunately, the existing operators can be utilized under strict limitations and constraints. In this manuscript, we focused on new prioritized aggregation operators which remove the strict limitations of the existing operators. The addition of reference parameters associated with membership and non-membership grades in the linear Diophantine Fuzzy sets provide a robust modeling for MCDM problems. The primary objective of this manuscript is to introduce new aggregation operators for modeling uncertainty by using linear Diophantine Fuzzy information. For this objective we develop aggregation operators (AO) namely, "linear Diophantine Fuzzy prioritized weighted average" (LDFPWA) operator and "linear Diophantine Fuzzy prioritized weighted geometric" (LDFPWG) operator. Certain essential properties of new prioritized AOs are also proposed. A secondary objective is to discuss a practical application of third party reverse logistic provider (3PRLP) optimization problem. The efficiency, superiority, and rationality of the proposed approach is analyzed by a numerical example to discuss 3PRLP. The symmetry of optimal decision and ranking of feasible alternatives is followed by a comparative analysis.

scholarly journals Multi-Attribute Decision Making Based on Probabilistic Neutrosophic Hesitant Fuzzy Choquet Aggregation Operators

Symmetry ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 623 ◽  
Author(s):  
Songtao Shao ◽  
Xiaohong Zhang ◽  
Quan Zhao
Keyword(s):  
Decision Making ◽  
Aggregation Operators ◽  
Decision Makers ◽  
Third Party ◽  
Optimal Decision ◽  
Third Party Logistics ◽  
The Third Party Logistics ◽  
External Space ◽  
The Third ◽  
Multi Attribute Decision Making

Take the third-party logistics providers (3PLs) as an example, according to the characteristics of correlation between attributes in multi-attribute decision-making, two Choquet aggregation operators adoping probabilistic neutrosophic hesitation fuzzy elements (PNHFEs) are proposed to cope with the situations of correlation among criterions. This measure not only provides support for the correlation phenomenon between internal attributes, but also fully concerns the incidental uncertainty of the external space. Our goal is to make it easier for decision makers to cope with this uncertainty, thus we establish the notion of probabilistic neutrosophic hesitant fuzzy Choquet averaging (geometric) (PNHFCOA, PNHFCOG) operator. Based on this foundation, a method for aggregating decision makers’ information is proposed, and then the optimal decision scheme is obtained. Finally, an example of selecting optimal 3PL is given to demonstrate the objectivity of the above-mentioned standpoint.

scholarly journals Bonferroni Prioritized Aggregation Operators Applied to Government Transparency

Mathematics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 24 ◽  
Author(s):  
Luis A. Perez-Arellano ◽  
Fabio Blanco-Mesa ◽  
Ernesto Leon-Castro ◽  
Victor Alfaro-Garcia
Keyword(s):  
Main Idea ◽  
Weighted Average ◽  
Aggregation Operator ◽  
Aggregation Operators ◽  
Decision Makers ◽  
Bonferroni Mean ◽  
Different Types ◽  
Ordered Weighted Average ◽  
Types Of Information ◽  
Prioritized Aggregation Operators

This article applies the Bonferroni prioritized induced heavy ordered weighted average (OWA) to analyze a series of data and focuses on the Bonferroni average and heavy induced prioritized aggregation operators. The objective of the present work is to present a new aggregation operator that combines the heavy induced prioritized Bonferroni and its formulations and represents the Bonferroni mean with variables that induce an order with vectors that are greater than one. This work develops some extensions using prioritization. The main advantage is that different types of information provided by a group of decision makers to compare real situations are included in this formulation. Finally, an example using the operators to calculate the transparency of the websites of the 32 states of Mexico was performed. The main idea was to visualize how the ranking can change depending on the importance of the five components of the methodology. The main results show that it is possible to detect some important changes depending on the operator and the experts considered.

scholarly journals Multigranular Uncertain Linguistic Prioritized Aggregation Operators and Their Application to Multiple Criteria Group Decision Making

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Ding-Hong Peng ◽  
Tie-Dan Wang ◽  
Chang-Yuan Gao ◽  
Hua Wang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Weighted Average ◽  
Aggregation Operators ◽  
Multiple Criteria ◽  
Linguistic Variables ◽  
Prioritized Aggregation Operator ◽  
Prioritized Aggregation Operators ◽  
Decision Elements

We investigate multiple criteria group decision-making problems in which there are priority relationships between the decision elements (criteria and experts), and decision information provided by decision makers takes the form of multigranular uncertain linguistic information. Firstly, some operational laws and possibility degree of multi-granular uncertain linguistic variables are introduced. Then, some new linguistic aggregation operators based on the prioritized aggregation operator, such as the multigranular uncertain linguistic prioritized weighted average (MULPWA) operator and the multigranular uncertain linguistic prioritized ordered weighted average (MULPOWA) operator, are developed and their desirable properties are studied. The prominent characteristics of these proposed operators are that they can aggregate directly the uncertain linguistic variables whose values form the linguistic term sets with different granularities and convey the prioritization phenomenon among the aggregated arguments. Furthermore, based on the MULPWA and MULPOWA operators, an approach to deal with multiple criteria group decision-making problems under multi-granular uncertain linguistic environments is developed. Finally, a practical example is provided to illustrate the multiple criteria group decision-making process.

scholarly journals Linear Diophantine Fuzzy Relations and Their Algebraic Properties with Decision Making

Symmetry ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 945
Author(s):  
Saba Ayub ◽  
Muhammad Shabir ◽  
Muhammad Riaz ◽  
Muhammad Aslam ◽  
Ronnason Chinram
Keyword(s):  
Decision Making ◽  
Real Life ◽  
Score Function ◽  
Fuzzy Relation ◽  
Optimal Decision ◽  
Fuzzy Relations ◽  
Binary Relations ◽  
Life Problems ◽  
Modeling Uncertainties ◽  
Novel Concept

Binary relations are most important in various fields of pure and applied sciences. The concept of linear Diophantine fuzzy sets (LDFSs) proposed by Riaz and Hashmi is a novel mathematical approach to model vagueness and uncertainty in decision-making problems. In LDFS theory, the use of reference or control parameters corresponding to membership and non-membership grades makes it most accommodating towards modeling uncertainties in real-life problems. The main purpose of this paper is to establish a robust fusion of binary relations and LDFSs, and to introduce the concept of linear Diophantine fuzzy relation (LDF-relation) by making the use of reference parameters corresponding to the membership and non-membership fuzzy relations. The novel concept of LDF-relation is more flexible to discuss the symmetry between two or more objects that is superior to the prevailing notion of intuitionistic fuzzy relation (IF-relation). Certain basic operations are defined to investigate some significant results which are very useful in solving real-life problems. Based on these operations and their related results, it is analyzed that the collection of all LDF-relations gives rise to some algebraic structures such as semi-group, semi-ring and hemi-ring. Furthermore, the notion of score function of LDF-relations is introduced to analyze the symmetry of the optimal decision and ranking of feasible alternatives. Additionally, a new algorithm for modeling uncertainty in decision-making problems is proposed based on LDFSs and LDF-relations. A practical application of proposed decision-making approach is illustrated by a numerical example. Proposed LDF-relations, their operations, and related results may serve as a foundation for computational intelligence and modeling uncertainties in decision-making problems.

scholarly journals Fuzzy covering location problems with different aggregation operators

Filomat ◽  
2017 ◽  
Vol 31 (2) ◽  
pp. 513-522 ◽  
Author(s):  
Darko Drakulic ◽  
Aleksandar Takaci ◽  
Miroslav Maric
Keyword(s):  
Combinatorial Optimization ◽  
Fuzzy Sets ◽  
Optimization Problems ◽  
Real Life ◽  
Aggregation Operators ◽  
Location Problems ◽  
Important Class ◽  
Combinatorial Optimization Problems ◽  
Life Problems ◽  
Standard Models

Covering location problems is well-known and very important class of combinatorial optimization problems. Standard models for covering location problems cannot encompass real-life problems, because real-life problems contain some degree of uncertainty. The use of fuzzy sets in modeling covering location problems allows the implementation of these conditions. Depending on the type of problems, it is necessary to use different aggregation operators in calculating solution?s quality. The aim of this study is introducing of fuzzy sets with different corresponding conorms in modeling most known types of covering location problems.

scholarly journals Decision-Making Approach Based on Generalized Aggregation Operators with Complex Single-Valued Neutrosophic Hesitant Fuzzy Set Information

2022 ◽  
Vol 2022 ◽  
pp. 1-20
Author(s):  
Harish Garg ◽  
Zeeshan Ali ◽  
Ibrahim M. Hezam ◽  
Jeonghwan Gwak
Keyword(s):  
Decision Making ◽  
Dominant Role ◽  
Real Life ◽  
Weighted Average ◽  
Aggregation Operators ◽  
Strategic Decision ◽  
Weighted Averaging ◽  
Hesitant Fuzzy Set ◽  
Efficient Manner ◽  
Novel Concept

A strategic decision-making technique can help the decision maker to accomplish and analyze the information in an efficient manner. However, in our real life, an uncertainty will play a dominant role during the information collection phase. To handle such uncertainties in the data, we present a decision-making algorithm under the single-valued neutrosophic (SVN) environment. The SVN is a powerful way to deal the information in terms of three degrees, namely, “truth,” “falsity,” and “indeterminacy,” which all are considered independent. The main objective of this study is divided into three folds. In the first fold, we state the novel concept of complex SVN hesitant fuzzy (CSVNHF) set by incorporating the features of the SVN, complex numbers, and the hesitant element. The various fundamental and algebraic laws of the proposed CSVNHF set are described in details. The second fold is to state the various aggregation operators to obtain the aggregated values of the considered CSVNHF information. For this, we stated several generalized averaging operators, namely, CSVNHF generalized weighted averaging, ordered weighted average, and hybrid average. The various properties of these operators are also stated. Finally, we discuss a multiattribute decision-making (MADM) algorithm based on the proposed operators to address the problems under the CSVNHF environment. A numerical example is given to illustrate the work and compare the results with the existing studies’ results. Also, the sensitivity analysis and advantages of the stated algorithm are given in the work to verify and strengthen the study.

Multi-Criteria Decision-Making Approach Based on Moderator Intuitionistic Fuzzy Hybrid Aggregation Operators

2019 ◽  
pp. 237-251
Author(s):  
Bhagawati Prasad Joshi ◽  
Akhilesh Singh
Keyword(s):  
Decision Making ◽  
Intuitionistic Fuzzy Set ◽  
Real Life ◽  
Aggregation Operators ◽  
Multi Criteria Decision Making ◽  
Intuitionistic Fuzzy ◽  
Life Problems ◽  
Uncertainty Index ◽  
Geometric Point ◽  
Membership Grade

It has been seen in literature that the notion of intuitionistic fuzzy sets (IFSs) is very powerful tool to deal with real life problems under the environment of uncertainty. This notion of IFSs favours the intermingling of the uncertainty index in membership functions. The uncertainty index is basically generated from a lot of parameters such as lack of awareness, historical information, situation, short of standard terminologies, etc. Hence, the uncertainty index appended finding the membership grade under IFSs needs additional enhancement. Then, the concept of a moderator intuitionistic fuzzy set (MIFS) is defined by adding a parameter in the IFSs environment to make the uncertain behaviour more accurate. In this chapter, some new moderator intuitionistic fuzzy hybrid aggregation operators are presented on the basis of averaging and geometric point of views to aggregate moderator intuitionistic fuzzy information. Then, a multi-criteria decision-making (MCDM) approach is provided and successfully implemented to real-life problems of candidate selection.

scholarly journals A Robust q-Rung Orthopair Fuzzy Einstein Prioritized Aggregation Operators with Application towards MCGDM

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1058 ◽  
Author(s):  
Muhammad Riaz ◽  
Hafiz Muhammad Athar Farid ◽  
Humaira Kalsoom ◽  
Dragan Pamučar ◽  
Yu-Ming Chu
Keyword(s):  
Decision Making ◽  
Group Decision ◽  
Real Life ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Membership Degree ◽  
Smooth Approximation ◽  
Life Circumstances ◽  
Significant Mechanism ◽  
Prioritized Aggregation Operators

A q-rung orthopair fuzzy set (q-ROFS) provides a significant mechanism for managing symmetrical aspects in real life circumstances. The renowned distinguishing feature of q-ROFS is that the sum of the qth powers to each membership degree (MD) and non-membership degree (NMD) is less than or equal 1, and therefore the comprehensive uncertain space for q-ROF information is broader. Numerous researchers have suggested several aggregation operators based on q-ROFSs. In order to discuss prioritized relationship in the criterion and a smooth approximation of q-ROF information, we introduced q-rung orthopair fuzzy Einstein prioritized weighted averaging (q-ROFEPWA) operator and q-rung orthopair fuzzy Einstein prioritized weighted geometric (q-ROFEPWG) operator. Additionally, we presented a multi-criteria group decision making (MCGDM) technique based on q-rung orthopair fuzzy Einstein prioritized aggregation operators. These operators can evaluate the possible symmetric roles of the criterion that express the real phenomena of the problem. In order to investigate characteristic of suggested operators regarding the symmetry of attributes and their symmetrical roles under q-ROF information, we presented an application of Einstein prioritized aggregation operators. Finally, by comparing it with some other established representative MCGDM models, an illustrative example is provided to check the feasibility, efficiency and supremacy of the proposed technique.

Prioritized Information Fusion Method for Triangular Fuzzy Information and Its Application to Multiple Attribute Decision Making

2016 ◽  
Vol 24 (02) ◽  
pp. 265-289 ◽  
Author(s):  
Rajkumar Verma ◽  
Bhudev Sharma
Keyword(s):  
Decision Making ◽  
Weighted Average ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Fuzzy Information ◽  
Fuzzy Environment ◽  
Multiple Attribute ◽  
Special Cases ◽  
Ordered Weighted Average ◽  
Prioritized Aggregation Operators

This study investigates the multiple attribute decision making under triangular fuzzy environment in which the attributes and experts are in different priority level. By combining the idea of quasi arithmetic mean and prioritized weighted average (PWA) operator, we first propose two new prioritized aggregation operators called quasi fuzzy prioritized weighted average (QFPWA) operator and the quasi fuzzy prioritized weighted ordered weighted average (QFPWOWA) operator for aggregating triangular fuzzy information. The properties of the new aggregation operators are studied in detail and their special cases are examined. Furthermore, based on the QFPWA operator and QFPWOWA operator, an approach to deal with multiple attribute decision-making problems under triangular fuzzy environments is developed. Finally, a practical example is provided to illustrate the multiple attribute decision making process.

Optimizing the Curriculum in Thermodynamics and Heat Transfer With Better Labs, In-Class Demonstrations and Interesting Realistic Problems to Enhance Learning

2015 ◽  
Author(s):  
K. Larsen ◽  
A. Hossain ◽  
M. Weiser
Keyword(s):  
Heat Transfer ◽  
Transfer Problem ◽  
Real Life ◽  
Primary Objective ◽  
Theoretical Understanding ◽  
Text Book ◽  
Life Problems ◽  
Class Room ◽  
Realistic Problem ◽  
Eastern Washington

The primary objective of a thermodynamic/heat transfer course is to provide the fundamental knowledge necessary to understand the behavior of thermal systems. A thermodynamic/heat transfer course provides a detailed calculus-based analysis of energy, entropy, exergy, conduction, convection, and radiation using these concepts to calculate the behavior and efficiencies of different processes and cycles. Proper conceptual and theoretical understanding of thermodynamics/heat transfer is very important to solve real life problems. In order to understand and properly use the concepts, it is necessary that there be effective labs and in-class demonstrations, as well as realistic problems to serve this purpose. Most thermodynamic/heat transfer courses have some labs and some courses use in-class demonstrations that attempt to apply what is being learned in the class room. How effective these labs and demonstrations are in helping the students understanding of the thermodynamic/heat transfer principles is questionable. To facilitate theoretical learning, instructors need to also solve a variety of interesting problems in thermodynamics/heat transfer, besides solving the conventional problems from the text book. Solving these realistic problems helps students to also enhance their conceptual understanding, and, motivate students to continue their learning. This paper describes an example of an interesting heat transfer problem that compares an analytical solution with that of an FEA solution to help engage the students in learning how to apply both approaches to a realistic problem. Furthermore, this paper discusses a series of labs that are currently used at Eastern Washington University (EWU) to help students apply what they are learning in a thermodynamic/heat transfer course. The labs at EWU are compared to a survey conducted at 25 universities to find other possible labs and in-class demonstrations. From this study, the best labs and in-class demonstrations will be discussed, explored, and implementation recommendations will be given.

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