Article
Computer Science, Artificial Intelligence
Irfan Deli
Summary: This work investigates multiple attribute decision-making problems with generalized trapezoidal hesitant fuzzy numbers, developing aggregation techniques and decision-making methods for analyzing and discussing decision processes under generalized trapezoidal hesitant fuzzy environments. The proposed approaches based on Bonferroni aggregation operators are applied to multicriteria decision making, with practical examples provided to illustrate the results, followed by a comparative analysis with existing methods.
Article
Mathematics
Wenying Wu, Zhiwei Ni, Feifei Jin, Jian Wu, Ying Li, Ping Li
Summary: A multiattribute group decision making method based on the generalized probabilistic hesitant fuzzy Bonferroni mean operator is proposed in this study to help decision-makers select appropriate parameters, and special aggregation operators for handling various parameter values are developed. The effectiveness and rationality of the method are validated through an investment case study.
Article
Materials Science, Multidisciplinary
Neha Ghorui, Arijit Ghosh, Sankar Prasad Mondal, Mohd Yazid Bajuri, Ali Ahmadian, Soheil Salahshour, Massimiliano Ferrara
Summary: The outbreak of the COVID-19 pandemic since December 2019 has significantly impacted global health and economy. To contain the virus, evaluating and ranking risk factors is crucial. This study utilized the FAHP methodology to determine weights and applied HFS with TOPSIS to identify the major risk factor as prolonged contact with infected individuals, spread through hospitals and clinics, and verbal transmission. The research demonstrated the application of MCDM tools for evaluating the most significant risk factor and conducted a sensitivity analysis.
RESULTS IN PHYSICS
(2021)
Article
Computer Science, Artificial Intelligence
Yibo Wang, Xiuqin Ma, Hongwu Qin, Huanling Sun, Weiyi Wei
Summary: This research presents the definition of hesitant Fermatean fuzzy Bonferroni mean operator (HFFBM) and derives the hesitant Fermatean fuzzy Einstein Bonferroni mean operator (HFFEBM) using basic operations of hesitant Fermatean fuzzy sets in Einstein t-norms. It also develops the hesitant Fermatean fuzzy weighted Bonferroni mean (HFFWBM) operator and the hesitant Fermatean fuzzy Einstein weighted Bonferroni mean operator (HFFEWBM), considering the influence of weights on decision-making outcomes. Moreover, a new multi-attribute decision-making (MADM) approach based on HFFWBM and HFFEWBM operator is provided and applied to a depression diagnostic evaluation with satisfactory results.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Multidisciplinary Sciences
Ayesha Sultan, Wojciech Salabun, Shahzad Faizi, Muhammad Ismail
Summary: In this paper, a hesitant fuzzy linear regression model (HFLRM) is proposed to solve multicriteria decision-making (MCDM) problems in a hesitant environment. The parameters of HFLRM are estimated through solving a linear programming (LP) model, using symmetric triangular fuzzy numbers (STFNs). An application example is presented to compare the effectiveness of HFLRM with the technique for order preference by similarity to ideal solution (TOPSIS), using Spearman's rank correlation test.
Article
Computer Science, Information Systems
Chenxia Jin, Jusheng Mi, Fachao Li, Meishe Liang
Summary: This study explores and applies the fusion of probabilistic hesitant fuzzy sets (PHFSs) and rough sets in uncertain multi-criteria decision-making (MCDM). It introduces an advanced method to obtain normalized PHFSs (NPHFSs), establishes a novel probabilistic hesitant fuzzy rough set (PHFRS) model, and proposes a fuzziness-based objective weight determination method. The effectiveness of the proposed method is demonstrated through experimental comparisons.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Chenxia Jin, Jusheng Mi, Fachao Li, Meishe Liang
Summary: Multi-criteria Decision Making (MCDM) is crucial in various application fields. To address the shortcomings of the TOPSIS method in ranking alternatives completely in a Hesitant Fuzzy beta-Covering Approximation Space (HF beta CAS), we propose an improved TOPSIS method. We define hesitant fuzzy relationships based on hesitant fuzzy beta-neighborhood and construct corresponding hesitant fuzzy covering rough set models. We also introduce a comprehensive weight determination method and develop a gamma-beta CHF-TOPSIS method for MCDM.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Computer Science, Artificial Intelligence
Tahir Mahmood, Muhammad Ahsen, Zeeshan Ali
Summary: Picture hesitant fuzzy sets are a valuable tool for expressing uncertain information, surpassing intuitionistic fuzzy sets and hesitant fuzzy sets in certain aspects. The proposed picture hesitant fuzzy mean operators offer a new method for dealing with decision-making in uncertain environments, with demonstrated effectiveness and superiority in practical examples.
Article
Green & Sustainable Science & Technology
Selvaraj Geetha, Samayan Narayanamoorthy, Joseph Varghese Kureethara, Dumitru Baleanu, Daekook Kang
Summary: The research introduces a novel decision making method called HPF-ELECTRE method, which extends the ELECTRE III method with HPF set for the plastic recycling problem. Plastic, being a non-biodegradable synthetic chemical, poses a serious threat to the environment and human life, highlighting the importance of finding suitable recycling methods. The HPF-ELECTRE III method, with its outranking based on concordance and discordance acceptability values, is proposed as an effective tool for addressing decision making problems in plastic recycling.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Computer Science, Artificial Intelligence
Lantian Liu, Xinxing Wu, Guanrong Chen
Summary: Based on closed operational laws in picture fuzzy numbers and strict triangular norms, this article extends the Bonferroni mean operator to the picture fuzzy environment. It proposes the picture fuzzy interactional Bonferroni mean, picture fuzzy interactional weighted Bonferroni mean, and picture fuzzy interactional normalized weighted Bonferroni mean operators. The article proves the properties of these operators and establishes a novel multicriteria decision making method under the picture fuzzy environment. The effectiveness of the method is demonstrated through its application in enterprise resource planning systems selection.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Mathematics
Lu Zhang, Yabin Shao, Ning Wang
Summary: This paper introduces interaction partitioned Bonferroni mean operators under the dual hesitant q-rung orthopair fuzzy environment. The proposed operators are based on the laws of q-rung orthopair fuzzy interaction, partitioned Bonferroni mean, and dual hesitant q-rung orthopair fuzzy sets. Several aggregation operators are presented, including the weighted interaction partitioned Bonferroni mean operator and the interaction partitioned geometric Bonferroni mean operator for dual hesitant q-rung orthopair fuzzy numbers. The properties and special cases of these operators are analyzed, and a multicriteria group decision-making method is proposed. An example is provided to demonstrate the superiority and feasibility of the proposed method compared to existing methods.
JOURNAL OF MATHEMATICS
(2023)
Article
Computer Science, Artificial Intelligence
Arun Sarkar, Animesh Biswas
Summary: In this paper, a new method is proposed for decision-making using BM and Dombi t-conorms and t-norms in a dual hesitant q-rung orthopair fuzzy environment. The decision-making process becomes more flexible and capable of capturing relationships among input parameters. Important properties of the operators and the effectiveness of using them to solve multi-criteria group decision-making problems under DH q-ROF contexts are discussed and demonstrated with illustrative examples.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Mathematics, Applied
Min Woo Jang, Jin Han Park, Mi Jung Son
Summary: In this paper, a new fuzzy information representation tool called probabilistic picture hesitant fuzzy sets (P-PHFSs) is proposed, which captures the probabilities of elements in hesitant fuzzy sets. The basic operational rules, comparison methods, and aggregation operators for P-PHFSs are defined, and an information fusion process is provided. Two MCDM methods under a probabilistic picture hesitant fuzzy environment are developed based on the proposed operators. Numerical examples are given to demonstrate the application and effectiveness of the proposed approaches.
Article
Physics, Multidisciplinary
Jawad Ali
Summary: A hesitant fuzzy set is helpful in describing uncertainty in everyday life, and hesitant fuzzy aggregation operators are mathematical tools for combining inputs into a single result. This work introduces the concepts of hesitant fuzzy partitioned Maclaurin symmetric mean and hesitant fuzzy weighted partitioned Maclaurin symmetric mean operators, and proposes a novel multiple criteria decision-making technique based on the latter operator.
Article
Computer Science, Artificial Intelligence
Gulcin Buyukozkan, Merve Guler
Summary: The quantity of data generated in supply chains increases with the complexity of processes, and the choice of appropriate SCA tools has a direct impact on company productivity. Multi-criteria decision-making methods can be used to address this selection issue.
APPLIED SOFT COMPUTING
(2021)
Article
Management
Decui Liang, Adjei Peter Darko, Zeshui Xu, Yinrunjie Zhang
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2020)
Article
Management
Decui Liang, Mingwei Wang, Zeshui Xu, Xu Chen
Summary: This study expands the classic Three-Way Decision (TWD) model by introducing the influence of regret psychology on decision-makers' risk behaviors and proposing a new risk Interval-Valued TWD model. Through simulation experiments, the impact of regret behavior on TWD is explored and the effectiveness of the new model is validated. The new model is applied to project resource allocation, improving decision flexibility under resource constraints.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2021)
Article
Computer Science, Artificial Intelligence
Mingwei Lin, Huibing Wang, Zeshui Xu
ARTIFICIAL INTELLIGENCE REVIEW
(2020)
Article
Computer Science, Artificial Intelligence
Huchang Liao, Cheng Zhang, Li Luo, Zeshui Xu, Jian-Bo Yang, Dong-Ling Xu
Article
Computer Science, Artificial Intelligence
Huchang Liao, Xiaomei Mi, Zeshui Xu
FUZZY OPTIMIZATION AND DECISION MAKING
(2020)
Article
Computer Science, Artificial Intelligence
Cheng Zhang, Huchang Liao, Li Luo, Zeshui Xu
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2020)
Article
Computer Science, Artificial Intelligence
Dejian Yu, Zeshui Xu, Xizhao Wang
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2020)
Article
Construction & Building Technology
Mingwei Lin, Chao Huang, Zeshui Xu
SUSTAINABLE CITIES AND SOCIETY
(2020)
Article
Computer Science, Information Systems
Mingwei Wang, Decui Liang, Zeshui Xu
INFORMATION SCIENCES
(2020)
Article
Management
Bo Li, Yixin Zhang, Zeshui Xu
Summary: The concept of limited interval-valued probabilistic linguistic term sets (-IVPLTSs) is proposed to address the information loss issue in the normalization process of PLTS. Basic operation laws and aggregation operators for -IVPLTSs are provided, and the membership degree is determined by the deviation degree through a programming model. Application of the method to airline service quality evaluation is discussed to verify its rationality.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2021)
Article
Computer Science, Information Systems
Xue Li, Hongfu Liu, Bin Zhu
INFORMATION SCIENCES
(2020)
Article
Computer Science, Information Systems
Bin Zhu, Dingfei Guo, Long Ren
Summary: With the popularity of social media, extracting consumer preferences from online consumer-generated content is crucial for product/service providers. However, existing approaches struggle with analyzing preferences over different attributes, hindering comprehensive understanding of consumer choice decisions. To address this, we propose a method that calculates attribute weights based on sentiment analysis and quadratic programming, and models the weights as hesitant judgments for improved recommendation accuracy.
INFORMATION & MANAGEMENT
(2022)
Article
Computer Science, Artificial Intelligence
Long Ren, Bin Zhu, Zeshui Xu
Summary: Understanding consumer preference is crucial for decision-making, but it is difficult to directly observe. We propose a method to convert online ratings into pairwise comparisons and develop an online optimization model to determine the ranking orders of products or services. Our learning algorithm, based on a continuous Exp strategy, efficiently handles dynamic rating information with arbitrary distribution. We also explore the impact of the learning rate on ranking order and provide a real-world application of a recommendation system.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Management
Xiang Deng, Xiang Cheng, Jing Gu, Zeshui Xu
Summary: Empirical research shows that companies pursuing sustainable development have higher credit ratings and lower equity costs. However, there is no consensus on sustainable development indicators or investment decision-making methods. This study introduces a set of indicators and an optimization-based consensus model to guide investors in assessing sustainable development enterprises, contributing a new approach to multi-attribute group decision-making problems in the literature.
GROUP DECISION AND NEGOTIATION
(2021)
Article
Operations Research & Management Science
Bo Li, Yi-Xin Zhang, Ze-Shui Xu
JOURNAL OF THE OPERATIONS RESEARCH SOCIETY OF CHINA
(2020)
