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Ren H, Zhou H. A novel Hellinger distance-based regret theory method for spherical fuzzy decision making model and its application in logistics. Sci Rep 2024; 14:13952. [PMID: 38886370 PMCID: PMC11183099 DOI: 10.1038/s41598-024-63876-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 06/03/2024] [Indexed: 06/20/2024] Open
Abstract
Actual decision making problems are often based on the company decision maker's behavior factors, such as risk attitude, subjective preference, etc. Regret theory can well express the behavior of the decision maker. In this pursuit, a novel decision making method was developed, based on the regret theory for the multi-attribute decision making problem, in which attribute values were expressed by spherical fuzzy numbers. Distance measurement not only has extensive applications in fields such as pattern recognition and image processing, but also plays an important role in the research of fuzzy decision theory. The existing distance measures of spherical fuzzy set either have special cases of anti-intuition or are more complex in calculation, so finding suitable distance measures is also an important research topic in the decision-making theory of spherical fuzzy set. For this reason, we first establish a new distance of spherical fuzzy sets based on Hellinger distance of probability distribution. A decision maker's perception utility value function is proposed using the new distance formula, which is used to measure the regretful and rejoice value. Then we establish an optimization model for solving the attribute weights, when the information of attribute weight was partially known. Subsequently, the comprehensive perceived utility values were utilized to rank the order of the alternatives. Finally, a numerical example of assessment of logistics providers is used to show that the new decision making method is effective and feasible.
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Affiliation(s)
- Haiping Ren
- Teaching Department of Basic Subjects, Jiangxi University of Science and Technology, Nanchang, 330013, China
| | - Hui Zhou
- School of Mathematics and Computer Science, Yichun University, Yichun, 336000, China.
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2
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Bin Azim A, Ali A, Khan AS, Awwad FA, Ismail EA, Ali S. Assessing indoor positioning system: A q-spherical fuzzy rough TOPSIS analysis. Heliyon 2024; 10:e31018. [PMID: 38778951 PMCID: PMC11108994 DOI: 10.1016/j.heliyon.2024.e31018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 05/03/2024] [Accepted: 05/09/2024] [Indexed: 05/25/2024] Open
Abstract
This study investigates advanced data collection methodologies and their implications for understanding employee and customer behavior within specific locations. Employing a comprehensive multi-criteria decision-making framework, we evaluate various technologies based on four distinct criteria and four technological alternatives. To identify the most effective technological solution, we employ the q-spherical fuzzy rough TOPSIS method, integrating three key parameters: lower set approximation, upper set approximation, and parameter q (where q ≥ 1). Our novel approach combines the TOPSIS method with q-spherical fuzzy rough set theory, providing deeper insights into data-driven decision-making processes in corporate environments. By comparing our proposed framework with existing multi-criteria decision-making methodologies, we demonstrate its strength and competitiveness. This research contributes to enhancing decision-making capabilities in corporate settings and beyond.
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Affiliation(s)
- Ahmad Bin Azim
- Department of Mathematics and Statistics, Hazara University Mansehra 21300, Khyber Pakhtunkhwa, Pakistan
| | - Asad Ali
- Department of Mathematics and Statistics, Hazara University Mansehra 21300, Khyber Pakhtunkhwa, Pakistan
| | - Abdul Samad Khan
- Research Center for Computational Science, School of Mathematics and Statistics, Northwestern Polytechnical University, Xi'an, 710129, China
| | - Fuad A. Awwad
- Department of Quantitative analysis, College of Business Administration, King Saud University, P.O. Box 71115, Riyadh, 11587, Saudi Arabia
| | - Emad A.A. Ismail
- Department of Quantitative analysis, College of Business Administration, King Saud University, P.O. Box 71115, Riyadh, 11587, Saudi Arabia
| | - Sumbal Ali
- Department of Mathematics and Statistics, Hazara University Mansehra 21300, Khyber Pakhtunkhwa, Pakistan
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3
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Haseli G, Sheikh R, Ghoushchi SJ, Hajiaghaei-Keshteli M, Moslem S, Deveci M, Kadry S. An extension of the best-worst method based on the spherical fuzzy sets for multi-criteria decision-making. GRANULAR COMPUTING 2024; 9:40. [PMID: 38585422 PMCID: PMC10996092 DOI: 10.1007/s41066-024-00462-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 02/03/2024] [Indexed: 04/09/2024]
Abstract
The ambiguous information in multi-criteria decision-making (MCDM) and the vagueness of decision-makers for qualitative judgments necessitate accurate tools to overcome uncertainties and generate reliable solutions. As one of the latest and most powerful MCDM methods for obtaining criteria weight, the best-worst method (BWM) has been developed. Compared to other MCDM methods, such as the analytic hierarchy process, the BWM requires fewer pairwise comparisons and produces more consistent results. Consequently, the main objective of this study is to develop an extension of BWM using spherical fuzzy sets (SFS) to address MCDM problems under uncertain conditions. Hesitancy, non-membership, and membership degrees are three-dimensional functions included in the SFS. The presence of three defined degrees allows decision-makers to express their judgments more accurately. An optimization model based on nonlinear constraints is used to determine optimal spherical fuzzy weight coefficients (SF-BWM). Additionally, a consistency ratio is proposed for the SF-BWM to assess the reliability of the proposed method in comparison to other versions of BWM. SF-BWM is examined using two numerical decision-making problems. The results show that the proposed method based on the SF-BWM provided the criteria weights with the same priority as the BWM and fuzzy BWM. However, there are differences in the criteria weight values based on the SF-BWM that indicate the accuracy and reliability of the obtained results. The main advantage of using SF-BWM is providing a better consistency ratio. Based on the comparative analysis, the consistency ratio obtained for SF-BWM is threefold better than the BWM and fuzzy BWM methods, which leads to more accurate results than BWM and fuzzy BWM.
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Affiliation(s)
- Gholamreza Haseli
- Tecnologico de Monterrey, School of Engineering and Sciences, Monterrey, Mexico
- School of Architecture Planning and Environmental Policy, University College Dublin, Belfield, Dublin, D04 V1W8 Ireland
| | - Reza Sheikh
- Faculty of Industrial Engineering and Management, Shahrood University of Technology, Shahrood, Iran
| | | | | | - Sarbast Moslem
- School of Architecture Planning and Environmental Policy, University College Dublin, Belfield, Dublin, D04 V1W8 Ireland
| | - Muhammet Deveci
- Department of Industrial Engineering, Turkish Naval Academy, National Defence University, 34942 Tuzla, Istanbul, Turkey
- The Bartlett School of Sustainable Construction, University College London, 1-19 Torrington Place, London, WC1E 7HB UK
- Department of Electronical and Computer Engineering, Lebanese American University, Byblos, Lebanon
| | - Seifedine Kadry
- Department of Applied Data Science, Noroff University College, Kristiansand, Norway
- Artificial Intelligence Research Center (AIRC), Ajman University, 346 Ajman, United Arab Emirates
- MEU Research Unit, Middle East University, Amman, 11831 Jordan
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4
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Ajay D, Selvachandran G, Aldring J, Thong PH, Son LH, Cuong BC. Einstein exponential operation laws of spherical fuzzy sets and aggregation operators in decision making. MULTIMEDIA TOOLS AND APPLICATIONS 2023:1-24. [PMID: 37362734 PMCID: PMC10090759 DOI: 10.1007/s11042-023-14532-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 05/21/2021] [Accepted: 01/31/2023] [Indexed: 06/28/2023]
Abstract
The spherical fuzzy set (SFS) model is one of the newly developed extensions of fuzzy sets (FS) for the purpose of dealing with uncertainty or vagueness in decision making. The aim of this paper is to define new exponential and Einstein exponential operational laws for spherical fuzzy sets and their corresponding aggregation operators. We introduce the operational laws for exponential and Einstein exponential SFSs in which the base values are crisp numbers and the exponents (weights) are spherical fuzzy numbers. Some of the properties and characteristics of the proposed operations are then discussed. Based on these operational laws, some new aggregation operators for the SFS model, namely Spherical Fuzzy Weighted Exponential Averaging (SFWEA) and Spherical Fuzzy Einstein Weighted Exponential Averaging (SFEWEA) operators are introduced. Finally, a decision-making algorithm based on these newly introduced aggregation operators is proposed and applied to a multi-criteria decision making (MCDM) problem related to ranking different types of psychotherapy.
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Affiliation(s)
- D. Ajay
- Department of Mathematics, Sacred Heart College, Tamilnadu, India
| | - Ganeshsree Selvachandran
- Institute of Actuarial Science and Data Analytics, UCSI University, Jalan Menara Gading, 56000 Cheras, Kuala Lumpur Malaysia
- Symbiosis Institute of Technology Symbiosis International University, Pune, 412115 India
| | - J. Aldring
- Department of Mathematics, Sacred Heart College, Tamilnadu, India
- Panimalar Engineering College, Department of Mathematics, Chennai, 600 123 Tamil Nadu India
| | - Pham Huy Thong
- VNU Information Technology Institute, Vietnam National University, Hanoi, Vietnam
| | - Le Hoang Son
- VNU Information Technology Institute, Vietnam National University, Hanoi, Vietnam
| | - Bui Cong Cuong
- Institute of Mathematics, Vietnam Academy of Science and Technology, Hanoi, Vietnam
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Wang J, Cai Q, Wang H, Wei G, Liao N. An integrated decision-making methodology for green supplier selection based on the improved IVIF-CPT-MABAC method. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2023. [DOI: 10.3233/jifs-224206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/09/2023]
Abstract
Green supply chain management attaches great importance to the coordinated development of social economy and ecological environment, and requires enterprises to consider environmental protection factors in product design, packaging, procurement, production, sales, logistics, waste and recycling. Suppliers are the “source” of the entire supply chain, and the choice of green suppliers is the basis of green supply chain management, and their quality will directly affect the environmental performance of enterprises. The green supplier selection is a classical multiple attribute group decision making (MAGDM) problems. Interval-valued intuitionistic fuzzy sets (IVIFSs) are the extension of intuitionistic fuzzy sets (IFSs), and are utilized to depict the complex and changeable circumstance. To better adapt to complex environment, the purpose of this paper is to construct a new method to solve the MAGDM problems for green supplier selection. Taking the fuzzy and uncertain character of the IVIFSs and the psychological preference into consideration, the original MABAC method based on the cumulative prospect theory (CPT) is extended into IVIFSs (IVIF-CPT-MABAC) method for MAGDM issues. Meanwhile, the method to evaluate the attribute weighting vector is calculated by CRITIC method. Finally, a numerical example for green supplier selection has been given and some comparisons is used to illustrate advantages of IVIF-CPT-MABAC method and some comparison analysis and sensitivity analysis are applied to prove this new method’s effectiveness and stability.
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Affiliation(s)
- Jing Wang
- School of Mathematical Sciences, Sichuan Normal University, Chengdu, P.R. China
| | - Qiang Cai
- School of Business, Sichuan Normal University, Chengdu, P.R. China
| | - Hongjun Wang
- School of Economics and Management, Chongqing University of Arts and Sciences, Chongqing, China
| | - Guiwu Wei
- School of Business, Sichuan Normal University, Chengdu, P.R. China
| | - Ningna Liao
- School of Business, Sichuan Normal University, Chengdu, P.R. China
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Zhang H, Wang H, Cai Q, Wei G. Spherical fuzzy hamacher power aggregation operators based on entropy for multiple attribute group decision making. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2023. [DOI: 10.3233/jifs-224468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
Abstract
As an improved form of fuzzy sets (FSs), spherical fuzzy sets (SFSs) could provide decision makers (DMs) with more free space to express their preference information. In this article, we first develop some Hamacher power aggregation operators under SFSs by power operators and Hamacher operators, including spherical fuzzy Hamacher power average (SFHPA) operator, spherical fuzzy Hamacher power geometric (SFHPG) operator, spherical fuzzy Hamacher power weighted average (SFHPWA) operator, spherical fuzzy Hamacher power weighted geometric (SFHPWG) operator, spherical fuzzy Hamacher power ordered weighted average (SFHPOWA) operator, spherical fuzzy Hamacher power ordered weighted geometric (SFHPOWG) operator, spherical fuzzy Hamacher power hybrid average (SFHPHA) operator and spherical fuzzy Hamacher power hybrid geometric (SFHPHG) operator. At the same time, some properties of the proposed operators are investigated, and the relationships between these operators and existing operators are discussed. Furthermore, a novel spherical fuzzy entropy measure is introduced to calculate unknown attribute weights. Then, some novel multiple attribute group decision making (MAGDM) methods are established by the proposed operators as well as entropy measure under SFSs. Lastly, the practicability of the presented methods is verified with a numerical case. Moreover, the robustness, availability and superiority for the developed methods are demonstrated via sensitivity analysis and further comparation with the existing methods.
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Affiliation(s)
- Huiyuan Zhang
- School of Mathematics and Statistics, Liupanshui Normal University, Liupanshui, Guizhou, China
- School of Mathematical Sciences, Sichuan Normal University, Chengdu, P.R. China
| | - Hongjun Wang
- School of Economics and Management, Chongqing University of Arts and Sciences, Chongqing, China
| | - Qiang Cai
- School of Business, Sichuan Normal University, Chengdu, P.R. China
| | - Guiwu Wei
- School of Business, Sichuan Normal University, Chengdu, P.R. China
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Liu S, He X, Chan FTS, Wang Z. An extended multi-criteria group decision-making method with psychological factors and bidirectional influence relation for emergency medical supplier selection. EXPERT SYSTEMS WITH APPLICATIONS 2022; 202:117414. [PMID: 35505673 PMCID: PMC9047565 DOI: 10.1016/j.eswa.2022.117414] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 03/08/2022] [Accepted: 04/25/2022] [Indexed: 05/28/2023]
Abstract
The COVID-19 pandemic outbreak spread rapidly worldwide, posing a severe threat to human life. Due to its unpredictability and destructiveness, the emergency has aroused great common in society. At the same time, the selection of emergency medical supplier is one of the critical links in emergency decision-making, so undertaking appropriate decision-making using scientific tools becomes the primary challenge when an emergency outbreak occurs. The multi criteria group decision-making (MCGDM) method is an applicable and common method for choosing supplier. Nevertheless, because emergency medical supplier selection should consider regarding many aspects, it is difficult for decision makers (DMs) to develop a comprehensive assessment method for emergency medical supplier. Therefore, few academics have focused on emergency situation research by the MCGDM method, and the existing MCGDM method has some areas for improvement. In view of this situation, in this study, we propose a new MCGDM method, which considers the bidirectional influence relation of the criteria, consensus and the psychological factors of DMs. It providers a good aid in emergency decision-making and it could apply to other types of MCGDM research. Firstly, DMs give their assessment in interval type-2 fuzzy sets (IT2FSs). Secondly, an extended IT2FSs assessment method and a novel ISM-BWM-Cosine Similarity-Max Deviation Method (IBCSMDM) are used for weighing all alternatives. The TODIM (an acronym for interactive and multi-criteria decision-making in Portuguese) can obtain the ranking results under different risk attenuation factors. Eventually, this extended IT2FSs-IBCSMDM-TODIM method is applied in a real case in Wuhan in the context of COVID-19 to illustrate the practicability and usefulness.
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Affiliation(s)
- Sen Liu
- School of Logistics, Yunnan University of Finance and Economics, Kunming 650221, China
| | - Xiaojun He
- School of Logistics, Yunnan University of Finance and Economics, Kunming 650221, China
| | - Felix T S Chan
- Department of Decision Sciences, Macau University of Science and Technology, Taipa, Macao
| | - Zhiyong Wang
- Yunnan University of Finance and Economics, Kunming 650221, China
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T-Spherical fuzzy ORESTE method based on cross-entropy measures and its application in multiple attribute decision-making. Soft comput 2022. [DOI: 10.1007/s00500-022-07287-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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9
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Information Measures Based on T-Spherical Fuzzy Sets and Their Applications in Decision Making and Pattern Recognition. AXIOMS 2022. [DOI: 10.3390/axioms11070302] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The T-spherical fuzzy set (TSFS) is a modification of the fuzzy set (FS), intuitionistic fuzzy set (IFS), Pythagorean fuzzy set (PyFS), q-rung orthopair fuzzy set (q-ROFS), and picture fuzzy set (PFS), with three characteristic functions: the membership degree (MD) denoted by S, the nonmembership degree (NMD) denoted by D, and the abstinence degree (AD) denoted by I. It can be used to solve problems of uncertain information with no restrictions. The distance measure (DM) is a tool that sums up the difference between points, while the similarity measure (SM) is a method applied to calculate the similarity between objects within an interval of [0,1]. The current work aims to introduce novel DMs and SMs in the environment of TSFSs to show the limitations of the previously defined DMs and SMs. The suggested DMs and SMs provide more room for all three degrees to be selected without restriction. We investigated the effectiveness of the proposed DMs and SMs by applying a pattern-recognition technique, and we determined their applicability for multicriteria decision making (MCDM) using numerical examples. The newly proposed DMs and SMs are briefly compared to existing DMs and SMs, and appropriate conclusions are drawn.
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10
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Sarucan A, Baysal ME, Engin O. A spherical fuzzy TOPSIS method for solving the physician selection problem. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2021. [DOI: 10.3233/jifs-219185] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The membership functions of the intuitionistic fuzzy sets, Pythagorean fuzzy sets, neutrosophic sets and spherical fuzzy sets are based on three dimensions. The aim is to collect the expert’s judgments. Physicians serve patients in the physician selection problem. It is difficult to measure the service’s quality due to the variability in patients’ preferences. The patients physician preference criteria is differing and uncertainties. Thus, solving this problem with fuzzy method is more appropriate. In this study, we considered the physician selection as a multi-criteria decision-making problem. Solving this problem, we proposed a spherical fuzzy TOPSIS method. We used the five alternatives and eight criteria. The application was performed in the neurology clinics of Konya city state hospitals. In addition, we solved the same problem by the intuitionistic fuzzy TOPSIS method. We compared the solutions of two methods with each other. We found that the spherical fuzzy TOPSIS method is effective for solving the physician selection problem.
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Affiliation(s)
- Ahmet Sarucan
- Industrial Engineering Department, Konya TechnicalUniversity, Konya, Turkey
| | - Mehmet Emin Baysal
- Industrial Engineering Department, Konya TechnicalUniversity, Konya, Turkey
| | - Orhan Engin
- Industrial Engineering Department, Konya TechnicalUniversity, Konya, Turkey
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Ozceylan E, Ozkan B, Kabak M, Dagdeviren M. A state-of-the-art survey on spherical fuzzy sets1. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2021. [DOI: 10.3233/jifs-219186] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
In addition to the well-known fuzzy sets, a novel type of fuzzy set called spherical fuzzy set (SFS) is recently introduced in the literature. SFS is the generalized structure over existing structures of fuzzy sets (intuitionistic fuzzy sets-IFS, Pythagorean fuzzy sets-PFS, and neutrosophic fuzzy sets-NFS) based on three dimensions (truth, falsehood, and indeterminacy) to provide a wider choice for decision-makers (DMs). Although the SFS has been introduced recently, the topic attracts the attention of academicians at a remarkable rate. This study is the expanded version of the authors’ earlier study by Ozceylan et al. [1]. A comprehensive literature review of recent and state-of-the-art papers is studied to draw a framework of the past and to shed light on future directions. Therefore, a systematic review methodology that contains bibliometric and descriptive analysis is followed in this study. 104 scientific papers including SFS in their titles, abstracts and keywords are reviewed. The papers are then analyzed and categorized based on titles, abstracts, and keywords to construct a useful foundation of past research. Finally, trends and gaps in the literature are identified to clarify and to suggest future research opportunities in the fuzzy logic area.
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Affiliation(s)
- Eren Ozceylan
- Industrial Engineering Department, Gaziantep University, Gaziantep, Turkey
| | - Baris Ozkan
- Industrial Engineering Department, Ondokuz Mayıs University, Samsun, Turkey
| | - Mehmet Kabak
- Industrial Engineering Department, Gazi University, Ankara, Turkey
| | - Metin Dagdeviren
- Industrial Engineering Department, Gazi University, Ankara, Turkey
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Park C, Ashraf S, Rehman N, Abdullah S, Aslam M. Evaluation of the product quality of the online shopping platform using t-spherical fuzzy preference relations. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2021. [DOI: 10.3233/jifs-202930] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
As a generalization of Pythagorean fuzzy sets and picture fuzzy sets, spherical fuzzy sets provide decision makers more flexible space in expressing their opinions. Preference relations have received widespread acceptance as an efficient tool in representing decision makers’ preference over alternatives in the decision-making process. In this paper, some new preference relations are investigated based on the spherical fuzzy sets. Firstly, the deficiency of the existing operating laws is elaborated in detail and three cases are described to identify the accuracy of the proposed operating laws in the context of t-spherical fuzzy environment. Also, a novel score function is proposed to obtain the consistent value in ranking of the alternatives. The backbone of this research, t-spherical fuzzy preference relation, consistent t-spherical fuzzy preference relations, incomplete t-spherical fuzzy preference relations, consistent incomplete t-spherical fuzzy preference relations, and acceptable incomplete t-spherical fuzzy preference relations are established. Additionally, some ranking and selection algorithms are established using the proposed novel score function and preference relations to tackle the uncertainty in real-life decision-making problems. Finally, evaluation of the product quality of the online shopping platform problem is demonstrated to show the applicability and reliability of proposed technique.
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Affiliation(s)
- Choonkil Park
- Research Institute for Natural Sciences, Hanyang University, Seoul, Korea
| | - Shahzaib Ashraf
- Department of Mathematics and Statistics, Bacha Khan University, Charsadda, Pakistan
| | - Noor Rehman
- Department of Mathematics and Statistics, Bacha Khan University, Charsadda, Pakistan
| | - Saleem Abdullah
- Department of Mathematics, Abdul Wali Khan University, Mardan, Pakistan
| | - Muhammad Aslam
- Department of Mathematics, College of Sciences, King Khalid University, Abha, Saudi Arabia
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Seyfi-Shishavan SA, Gündoğdu FK, Farrokhizadeh E. An assessment of the banking industry performance based on Intuitionistic fuzzy Best-Worst Method and fuzzy inference system. Appl Soft Comput 2021. [DOI: 10.1016/j.asoc.2021.107990] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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14
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Mahmood T, Warraich MS, Ali Z, Pamucar D. Generalized MULTIMOORA method and Dombi prioritized weighted aggregation operators based on T‐spherical fuzzy sets and their applications. INT J INTELL SYST 2021. [DOI: 10.1002/int.22474] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Tahir Mahmood
- Department of Mathematics and Statistics International Islamic University Islamabad Islamabad Pakistan
| | - Muhammad S. Warraich
- Department of Mathematics and Statistics International Islamic University Islamabad Islamabad Pakistan
| | - Zeeshan Ali
- Department of Mathematics and Statistics International Islamic University Islamabad Islamabad Pakistan
| | - Dragan Pamucar
- Department of Logistics, Military Academy University of Defence in Belgrade Belgrade Serbia
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15
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A modified failure modes and effects analysis using interval-valued spherical fuzzy extension of TOPSIS method: case study in a marble manufacturing facility. Soft comput 2021. [DOI: 10.1007/s00500-021-05605-8] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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