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Chen S, Ren J, Ye K, Li F. A generalized interval-valued p,q Rung orthopair fuzzy Maclaurin symmetric mean and modified regret theory based sustainable supplier selection method. Sci Rep 2024; 14:14942. [PMID: 38942771 DOI: 10.1038/s41598-024-64765-3] [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: 03/05/2024] [Accepted: 06/12/2024] [Indexed: 06/30/2024] Open
Abstract
A novel interval valued p,q Rung orthopair fuzzy (IVPQ-ROF) multiple attribute group decision making (MAGDM) method for sustainable supplier selection (SSS) is proposed in this paper. This study mainly contains two research points: (1) tackling the interrelation between attributes; and (2) describing the psychological state and risk attitude of decision makers (DMs). For the first research point, we introduce the Archimedean operation rules for interval valued p,q Rung orthopair fuzzy sets (IVPQ-ROFSs), then the generalized interval valued p, q Rung orthopair fuzzy Maclaurin symmetric mean (GIVPQ-ROFMSM) operator and the generalized interval valued p, q Rung orthopair fuzzy weighted Maclaurin symmetric mean (GIVPQ-ROFWMSM) operator are defined to reflect the correlation between attributes. For the second research point, we introduce the positive ideal degree (PID) and negative ideal degree (NID) based on projection of IVPQ-ROFSs, and modified regret theory. Both of them consider the best alternative and worst alternative, so as to reflect the psychological state and risk attitude of DMs. Finally, a SSS problem is presented to manifest the effectiveness of the designed method. We also provide sensitivity analysis and comparative analysis to further demonstrate the rationality and validity of the proposed method.
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Affiliation(s)
- Shuang Chen
- School of Advanced Interdisciplinary Studies, Hunan University of Technology and Business, No.569, Yuelu Avenue, Changsha, 410205, China
| | - Jian Ren
- School of Advanced Interdisciplinary Studies, Hunan University of Technology and Business, No.569, Yuelu Avenue, Changsha, 410205, China.
- Xiangjiang Laboratory, Hunan University of Technology and Business, No.569, Yuelu Avenue, Changsha, 410205, China.
- Research Center for Smart Management of Resource and Environment, No.569, Yuelu Avenue, Changsha, 410205, China.
- Social Laboratory for Artificial Intelligence in Changsha, No.569, Yuelu Avenue, Changsha, 410205, China.
| | - KeTing Ye
- School of Advanced Interdisciplinary Studies, Hunan University of Technology and Business, No.569, Yuelu Avenue, Changsha, 410205, China
| | - FeiYan Li
- School of Advanced Interdisciplinary Studies, Hunan University of Technology and Business, No.569, Yuelu Avenue, Changsha, 410205, China
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Zhang F, Li M, Ye Z, Niu Y. A multi-stage group decision making approach for sustainable supplier selection based on probabilistic linguistic time-ordered incentive operator. PLoS One 2023; 18:e0293019. [PMID: 37906603 PMCID: PMC10617744 DOI: 10.1371/journal.pone.0293019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 10/04/2023] [Indexed: 11/02/2023] Open
Abstract
This study proposes a novel multi-stage multi-attribute group decision making method under a probabilistic linguistic environment considering the development state and trend of alternatives. First, the probabilistic linguistic term set (PLTS) is used by decision makers (DMs) to describe qualitative evaluation information. Subsequently, the weights of DMs for different attributes in different periods are determined by the credibility degree, which is combined with the hesitancy degree and the similarity degree. The evaluations of different DMs for alternatives and the evaluations of DMs' intentions to reward or punish are then aggregated. Later, the trend change level and the trend change stability of alternatives are measured through the means of reward and punishment incentives. Additionally, the probabilistic linguistic time-ordered incentive operator is proposed to aggregate the development state evaluation information and development trend evaluation information in different periods, and alternatives are prioritized by the extended TOPSIS method in the probabilistic linguistic environment. Finally, the practical use of the proposed decision framework is validated by using a sustainable supplier selection problem, and the effectiveness and the applicability of the framework are discussed through comparative analysis. The results show that the proposed approach can select suitable sustainable suppliers by considering their development state and trend in multiple stages.
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Affiliation(s)
- Faming Zhang
- Business School, Guilin University of Electronic Technology, Guilin, China
| | - Meixing Li
- Business School, Guilin University of Electronic Technology, Guilin, China
| | - Zhaoqing Ye
- College of Foreign Studies, Guilin University of Electronic Technology, Guilin, China
| | - Yufei Niu
- School of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou, China
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Riaz M, Farid HMA, Razzaq A, Simic V. A new approach to sustainable logistic processes with q-rung orthopair fuzzy soft information aggregation. PeerJ Comput Sci 2023; 9:e1527. [PMID: 37705646 PMCID: PMC10495956 DOI: 10.7717/peerj-cs.1527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 07/20/2023] [Indexed: 09/15/2023]
Abstract
In recent years, as corporate consciousness of environmental preservation and sustainable growth has increased, the importance of sustainability marketing in the logistic process has grown. Both academics and business have increased their focus on sustainable logistics procedures. As the body of literature expands, expanding the field's knowledge requires establishing new avenues by analyzing past research critically and identifying future prospects. The concept of "q-rung orthopair fuzzy soft set" (q-ROFSS) is a new hybrid model of a q-rung orthopair fuzzy set (q-ROFS) and soft set (SS). A q-ROFSS is a novel approach to address uncertain information in terms of generalized membership grades in a broader space. The basic alluring characteristic of q-ROFS is that they provide a broader space for membership and non-membership grades whereas SS is a robust approach to address uncertain information. These models play a vital role in various fields such as decision analysis, information analysis, computational intelligence, and artificial intelligence. The main objective of this article is to construct new aggregation operators (AOs) named "q-rung orthopair fuzzy soft prioritized weighted averaging" (q-ROFSPWA) operator and "q-rung orthopair fuzzy soft prioritized weighted geometric" (q-ROFSPWG) operator for the fusion of a group of q-rung orthopair fuzzy soft numbers and to tackle complexities and difficulties in existing operators. These AOs provide more effective information fusion tools for uncertain multi-attribute decision-making problems. Additionally, it was shown that the proposed AOs have a higher power of discriminating and are less sensitive to noise when it comes to evaluating the performances of sustainable logistic providers.
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Affiliation(s)
- Muhammad Riaz
- Department of Mathematics, University of the Punjab, Lahore, Punjab, Pakistan
| | | | - Ayesha Razzaq
- Department of Mathematics, University of the Punjab, Lahore, Punjab, Pakistan
| | - Vladimir Simic
- Faculty of Transport and Traffic Engineering, University of Belgrade, Belgrade, Serbia
- College of Engineering, Department of Industrial Engineering and Management, Yuan Ze University, Taoyuan, Taiwan
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Wan G, Rong Y, Garg H. An efficient spherical fuzzy MEREC-CoCoSo approach based on novel score function and aggregation operators for group decision making. GRANULAR COMPUTING 2023; 8:1-23. [PMID: 38625159 PMCID: PMC10184975 DOI: 10.1007/s41066-023-00381-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 04/15/2023] [Indexed: 04/17/2024]
Abstract
The major objective of the current investigation is to build an integrated multiple criteria group decision-making (MCGDM) methodology based on combined compromise solution (CoCoSo) and spherical fuzzy set for determining the optimal solar power station. To begin with, an innovative spherical fuzzy score function is brought forward to strengthen the efficiency of the comparison for spherical fuzzy number (SFN). Secondly, several newly operational laws for SFN are defined and some novel aggregation operation based on them are propounded. The corresponding excellent properties of the novel operators are also explored at length. Further, the spherical fuzzy method on the removal effects of criteria (MEREC) technique is presented by the proposed score function to work out the importance of the criteria. Lastly, an MCGDM approach is propounded based on improved spherical fuzzy CoCoSo to obtain the ranking of the solar power station locations. The feasibility and practicability of the proposed SF-MEREC-CoCoSo method are investigated through the comparison study with the extant methods. The sensibility analysis is also executed to discuss the robustness and stability of the propounded methodology.
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Affiliation(s)
- Guorou Wan
- Department of Basic Education, Sichuan College of Architectural Technology, Deyang, 618000 China
| | - Yuan Rong
- School of Management, Shanghai University, Shanghai, 200444 China
| | - Harish Garg
- School of Mathematics, Thapar Institute of Engineering and Technology (Deemed University), Patiala, Punjab 147004 India
- Department of Mathematics, Graphics Era Deemed to Be University, Dehradun, Uttarakhand 248002 India
- Applied Science Research Center, Applied Science Private University, Amman, 11931 Jordan
- College of Technical Engineering, The Islamic University, Najaf, Iraq
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Liu L, Zhu Q, Yang D, Liu S. Extended Multicriteria Group Decision Making with a Novel Aggregation Operator for Emergency Material Supplier Selection. ENTROPY (BASEL, SWITZERLAND) 2023; 25:e25040702. [PMID: 37190490 PMCID: PMC10137439 DOI: 10.3390/e25040702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 04/14/2023] [Accepted: 04/17/2023] [Indexed: 05/17/2023]
Abstract
How to ensure the normal production of industries in an uncertain emergency environment has aroused a lot of concern in society. Selecting the best emergency material suppliers using the multicriteria group decision making (MCGDM) method will ensure the normal production of industries in this environment. However, there are few studies in emergency environments that consider the impact of the decision order of decision makers (DMs) on the decision results. Therefore, in order to fill the research gap, we propose an extended MCGDM method, whose main steps include the following: Firstly, the DMs give their assessment of all alternatives. Secondly, we take the AHP method and entropy weight method to weight the criteria and the DMs. Thirdly, we take the intuitionistic fuzzy hybrid priority weight average (IFHPWA) operator we proposed to aggregate evaluation information and take the TOPSIS method to rank all the alternatives. Finally, the proposed method is applied in a case to prove its practicability and effectiveness. The proposed method considers the influence of the decision order of the DMs on the decision results, which improves the accuracy and efficiency of decision-making results.
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Affiliation(s)
- Ling Liu
- School of Logistics and Management Engineering, Yunnan University of Finance and Economics, Kunming 650221, China
| | - Qiuyi Zhu
- School of Logistics and Management Engineering, Yunnan University of Finance and Economics, Kunming 650221, China
| | - Dan Yang
- College of Innovative Business and Accountancy, Dhurakij Pundit University, Bangkok 10210, Thailand
| | - Sen Liu
- School of Logistics and Management Engineering, Yunnan University of Finance and Economics, Kunming 650221, China
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Pei M, Liu S, Wen H, Wang W. A developed gained and lost dominance score method for risk prioritization in FMEA with Fermatean fuzzy information. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2023. [DOI: 10.3233/jifs-222692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
Failure mode and effect analysis (FMEA) is one of the most effective means for potential systematic risk assessment in a real work environment. Nevertheless, the traditional FMEA approach has been extensively criticized for many deficiencies in coping with risk evaluation and prioritization problems under inter-uncertain environments. To overcome the limitations, in this paper, a synthesized risk priority calculation framework is proposed for FMEA by combining the gained and lost dominance score (GLDS) method, the combination ordered weighted averaging (C-OWA) operator, and Fermatean fuzzy set (FFS). Firstly, we use FFS to express the experts’ uncertain risk evaluation information which can depict the fuzziness and ambiguity of the information. Secondly, the C-OWA operator combined with FFS is introduced to build the group risk matrix which can provide a more reasonable risk analysis result. Then, the developed GLDS method with FFS is presented to calculate the risk priority of each failure mode which takes both individual and group risk attitudes into consideration. Finally, a medical device risk analysis case is introduced to demonstrate the proposed FMEA framework. We also perform comparison analyses to confirm the effectiveness and rationality of the hybrid risk prioritization framework for FMEA under a complex and uncertain situation.
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Affiliation(s)
- Mengjiao Pei
- School of Economics and Management, Anhui Normal University, Wuhu, Anhui, China
| | - Shuli Liu
- School of Economics and Management, Anhui Normal University, Wuhu, Anhui, China
- Yangtze River Delta Development Research Institute, Anhui Normal University, Wuhu, Anhui, China
| | - Haolan Wen
- School of Economics and Management, Anhui Normal University, Wuhu, Anhui, China
| | - Weizhong Wang
- School of Economics and Management, Anhui Normal University, Wuhu, Anhui, China
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Sharaf IM. The differential measure for Pythagorean fuzzy multiple criteria group decision-making. COMPLEX INTELL SYST 2022; 9:3333-3354. [PMID: 36530758 PMCID: PMC9734832 DOI: 10.1007/s40747-022-00913-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 11/06/2022] [Indexed: 12/12/2022]
Abstract
Pythagorean fuzzy sets (PFSs) proved to be powerful for handling uncertainty and vagueness in multi-criteria group decision-making (MCGDM). To make a compromise decision, comparing PFSs is essential. Several approaches were introduced for comparison, e.g., distance measures and similarity measures. Nevertheless, extant measures have several defects that can produce counter-intuitive results, since they treat any increase or decrease in the membership degree the same as the non-membership degree; although each parameter has a different implication. This study introduces the differential measure (DFM) as a new approach for comparing PFSs. The main purpose of the DFM is to eliminate the unfair arguments resulting from the equal treatment of the contradicting parameters of a PFS. It is a preference relation between two PFSs by virtue of position in the attribute space and according to the closeness of their membership and non-membership degrees. Two PFSs are classified as identical, equivalent, superior, or inferior to one another giving the degree of superiority or inferiority. The basic properties of the proposed DFM are given. A novel method for multiple criteria group decision-making is proposed based on the introduced DFM. A new technique for computing the weights of the experts is developed. The proposed method is applied to solve two applications, the evaluation of solid-state drives and the selection of the best photovoltaic cell. The results are compared with the results of some extant methods to illustrate the applicability and validity of the method. A sensitivity analysis is conducted to examine its stability and practicality.
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Affiliation(s)
- Iman Mohamad Sharaf
- Department of Basic Sciences, Higher Technological Institute, Tenth of Ramadan City, Egypt
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