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Lu K, Liao H. A survey of group decision making methods in Healthcare Industry 4.0: bibliometrics, applications, and directions. APPL INTELL 2022. [DOI: 10.1007/s10489-021-02909-y 10.1007/s10489-021-02909-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2022]
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Yan B, Wang Y, Xia W, Hu X, Ma H, Jin P. An improved method for satellite emergency mission scheduling scheme group decision-making incorporating PSO and MULTIMOORA. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2022. [DOI: 10.3233/jifs-212034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Satellite emergency mission scheduling scheme group decision making (SEMSSGDM) is a key part of satellite mission scheduling research. An appropriate evaluation model can provide a dependable and sustainable improvement and guide the functioning of emergency mission scheduling. Consequently, this research is devoted to proposing a novel decision-making method that employs a novel consensus model with hesitant fuzzy 2-tuple linguistic sets (HF2TLSs) to eliminate disagreements among satellite dispatchers and reach consensus in scheme decision-making. Within the novel method, it proposes a distance measurement function based on Hausdorff distance with HF2TLS to gauge the fit and similarity across satellite dispatchers. Additionally, a consensus reaching process (CRP) is designed to adjust the judgement of satellite dispatchers taking into account the trust degree to improve consensus. Within the selection process, a combination of the particle swarm optimization (PSO) algorithm and the MULTIplicative MOORA (MULTIMOORA) method is applied, where PSO is performed to improve the accuracy of information aggregation, and the MULTIMOORA method is used to develop the robustness of the selection results. Lastly, an applicative example validates the effectiveness of the method based on a mission scheduling intelligent decision simulation system.
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Affiliation(s)
- Bing Yan
- School of Management, Hefei University of Technology, Hefei, P.R. China
- Key Laboratory of Process Optimization and Intelligent Decision Making, Ministry of Education, Hefei, P.R. China
| | - Yanjun Wang
- School of Management, Hefei University of Technology, Hefei, P.R. China
- Key Laboratory of Process Optimization and Intelligent Decision Making, Ministry of Education, Hefei, P.R. China
| | - Wei Xia
- School of Management, Hefei University of Technology, Hefei, P.R. China
- Key Laboratory of Process Optimization and Intelligent Decision Making, Ministry of Education, Hefei, P.R. China
| | - Xiaoxuan Hu
- School of Management, Hefei University of Technology, Hefei, P.R. China
- Key Laboratory of Process Optimization and Intelligent Decision Making, Ministry of Education, Hefei, P.R. China
- Intelligent Interconnected Systems Laboratory of Anhui Province, China
| | - Huawei Ma
- School of Management, Hefei University of Technology, Hefei, P.R. China
- Key Laboratory of Process Optimization and Intelligent Decision Making, Ministry of Education, Hefei, P.R. China
| | - Peng Jin
- School of Management, Hefei University of Technology, Hefei, P.R. China
- Key Laboratory of Process Optimization and Intelligent Decision Making, Ministry of Education, Hefei, P.R. China
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Evaluation of small and medium-sized enterprises’ sustainable development with hesitant fuzzy linguistic group decision-making method. APPL INTELL 2022. [DOI: 10.1007/s10489-021-02372-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Lu K, Liao H. A survey of group decision making methods in Healthcare Industry 4.0: bibliometrics, applications, and directions. APPL INTELL 2022; 52:13689-13713. [PMID: 35002080 PMCID: PMC8727077 DOI: 10.1007/s10489-021-02909-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/05/2021] [Indexed: 12/07/2022]
Abstract
Healthcare Industry 4.0 refers to intelligent operation processes in the medical industry. With the development of information technology, large-scale group decision making (GDM), which allows a larger number of decision makers (DMs) from different places or sectors to participate in decision making, has been rapidly developed and applied in Healthcare Industry 4.0 to help to make decisions efficiently and smartly. To make full use of GDM methods to promote the developments of the medical industry, it is necessary to review the existing relevant achievements. Therefore, this paper conducts an overview to generate a comprehensive understanding of GDM in Healthcare Industry 4.0 and to identify future development directions. Bibliometric analyses are conducted in order to learn the development trends from published papers. The implementations of GDM methods in Healthcare Industry 4.0 are reviewed in accordance with the paradigm of the general GDM process, which includes information representation, dimension reduction, consensus reaching, and result elicitation. We also provide current research challenges and future directions regarding medical GDM. It is hoped that our study will be helpful for researchers in the field of GDM in Healthcare Industry 4.0.
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Affiliation(s)
- Keyu Lu
- Business School, Sichuan University, Chengdu, 610064 China
| | - Huchang Liao
- Business School, Sichuan University, Chengdu, 610064 China
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Krishankumar R, Arun K, Kumar A, Rani P, Ravichandran KS, Gandomi AH. Double-hierarchy hesitant fuzzy linguistic information-based framework for green supplier selection with partial weight information. Neural Comput Appl 2021. [DOI: 10.1007/s00521-021-06123-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Chen TY. The likelihood-based optimization ordering model for multiple criteria group decision making with Pythagorean fuzzy uncertainty. Neural Comput Appl 2020. [DOI: 10.1007/s00521-020-05278-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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