Article
Multidisciplinary Sciences
Ximei Hu, Shuxia Yang, Ya-Ru Zhu
Summary: This paper studies a new method for multiple attribute decision making with linguistic attributes and associations between attributes. A new linguistic generalized weighted Heronian mean is proposed, along with its properties. Multi-attribute decision making methods based on this mean are provided, and an analysis of an example compared with other methods is conducted.
Article
Computer Science, Artificial Intelligence
Qingzhao Li, Yuan Rong, Zheng Pei, Fangling Ren
Summary: One of the characteristics of large-scale linguistic decision making problems is that decision information is derived from multiple sources. In addition, the number of decision makers, alternatives or criteria in the context of big data is increasingly large. Correlation analysis between decision making attributes has become an important issue. The paper proposes a new similarity measure, linguistic intuitionistic fuzzy reducible weighted Maclaurin symmetric mean (LIFRWMSM) operator, and linguistic intuitionistic fuzzy reducible weighted dual Maclaurin symmetric mean (LIFRWDMSM) operator to deal with large-scale linguistic intuitionistic fuzzy decision making problems.
Article
Mathematics
Ximei Hu, Shuxia Yang, Ya-Ru Zhu
Summary: This paper investigates the application of Heronian mean and its derived operators in multiple attribute decision-making. A new three-parameter generalized weighted Heronian mean and intuitionistic fuzzy three-parameter generalized weighted Heronian mean are proposed with corresponding properties and methods. The research shows that these methods can effectively address the aggregation problem of attributes with correlation relationships.
Article
Multidisciplinary Sciences
Bowen Hou, Yongming Chen
Summary: This paper proposes a novel generalized orthopair fuzzy multi-attribute decision-making method, which combines the power average operator and the Bonferroni mean operator along with weight indicators to comprehensively and accurately represent fuzzy information in multi-attribute decision-making problems. The effectiveness of this operator is demonstrated, and its desirable properties are discussed.
Article
Mathematics, Applied
Tao Li, Liyuan Zhang
Summary: This paper addresses the multiple-attribute group decision-making problem using intuitionistic multiplicative linguistic variables (IMLVs). New operational laws and aggregation operators for IMLVs are introduced. Consistent IMLPR is defined, and a mathematical programming model is built to obtain the priority weight vector. An automatic convergent algorithm is designed to repair inconsistent IMLPR. Additionally, a model is established to estimate unknown values of an incomplete IMLPR. The proposed method is applied to practical problems and compared with existing approaches.
COMPUTATIONAL & APPLIED MATHEMATICS
(2022)
Article
Engineering, Multidisciplinary
Tahir Mahmood, Zeeshan Ali, Dulyawit Prangchumpol, Thammarat Panityakul
Summary: Neutrosophic sets have a greater power than fuzzy sets, with the ability to account for true, false, or indeterminate components. However, simultaneous variations can make neutrosophic sets unsuitable for certain circumstances. By combining multi-valued neutrosophic uncertain linguistic sets and complex fuzzy sets, the concept of multi-valued complex neutrosophic uncertain linguistic sets is developed to address these issues.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2022)
Article
Mathematics
Wei Yang, Yongfeng Pang
Summary: In this paper, T-spherical fuzzy Bonferroni mean operators are developed by extending the Bonferroni mean and Dombi mean to a T-Spherical fuzzy environment, to deal with complicated decision problems. Several T-spherical fuzzy Bonferroni mean operators are proposed, and their properties are studied. A new decision making method based on these operators is also proposed.
Article
Computer Science, Artificial Intelligence
Abhijit Saha, Harish Garg, Debjit Dutta
Summary: This study proposed a multicriteria group decision-making methodology based on probabilistic linguistic q-rung orthopair fuzzy sets, introducing two new operators and discussing methods for calculating subjective and objective weights of experts, as well as measuring criteria weights. The stability of the model was validated through a case study and sensitivity analysis, and comparisons were made with other existing schemes.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Chuanyang Ruan, Xiangjing Chen, Shouzhen Zeng, Shahbaz Ali, Bander Almutairi
Summary: This paper focuses on the influence of support degree and weight between different attributes on the decision-making process. The proposed operators improve the generalization ability and a MADM method is proposed based on these operators. The validity and viability of the new approach are demonstrated through an example.
Article
Computer Science, Artificial Intelligence
Peide Liu, Weiqiao Liu
Summary: The paper introduces the dual generalized weighted Bonferroni mean operator and the dual generalized weighted Bonferroni geometric mean operator for 2DULVs, aiming to handle multi-attribute decision making problems. By combining different operators, the approach demonstrates validity and superiority through illustrative examples and comparisons with other methods.
ARTIFICIAL INTELLIGENCE REVIEW
(2021)
Article
Multidisciplinary Sciences
Zheng Dong, Yushui Geng
Summary: This paper focuses on solving multiple-attribute group decision-making problems under a trapezoid intuitionistic fuzzy linguistic environment, proposing new aggregation operators and verifying the effectiveness and feasibility of the proposed approaches through a numerical example.
Article
Automation & Control Systems
Yi Yang, Feifan Yang, Guodong Yi, Danxia Xia, Jieyue Li
Summary: The aim of this paper is to develop a novel approach to aggregating online product ratings, providing consumers with useful decision-making knowledge and more credible product rankings. The credibility model supports individual weight allocation by mining personalized characteristics from rating information. The proposed method uses the IFINWIBM operator to aggregate multidimensional product ratings, and includes a learning mechanism for operator parameters to describe attribute interaction degree. The developed online multidimensional ratings aggregation decision-making model effectively solves the product ranking problem and is demonstrated through a numerical example and comparative analysis.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Automation & Control Systems
Yuan Rong, Yi Liu, Zheng Pei
Summary: This paper introduces interval-valued intuitionistic fuzzy sets and methods related to them, including BM operators based on ACC. By studying new operational rules and multi-attribute decision-making, a method for aggregating IVIFNs is proposed, and the effectiveness and superiority of the method are demonstrated.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2021)
Article
Mathematics, Applied
Jeevaraj Selvaraj, Prakash Gatiyala, Sarfaraz Hashemkhani Zolfani
Summary: The use of intuitionistic fuzzy numbers and aggregation operators in decision-making problems effectively addresses uncertainty and incompleteness in information, with trapezoidal intuitionistic fuzzy numbers, Heronian mean operator, and power average operator being commonly used methods. The study also suggests that new aggregation operators can combine the properties of different operators to enhance problem-solving efficiency.
Article
Multidisciplinary Sciences
Hongbing Song, Yushui Geng
Summary: In this paper, the Maclaurin symmetric mean (MSM) operator is combined with single-valued neutrosophic uncertain linguistic set to propose new operators, introducing weighted methods as well. The effectiveness and superiority of the method are verified through an investment example study.
Article
Management
Peide Liu, Hongxue Xu
Summary: This paper proposes an improved SuperSBM-Undesirable model and integrates it with the SBM-Undesirable model to differentiate DMUs in a one-stage model. The proposed model has advantages in computational time and considers the importance and weighted preference of undesirable outputs.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2023)
Article
Computer Science, Artificial Intelligence
Peide Liu, Ayad Hendalianpour, Mitra Forouzandeh Hafshejani, Farideh Yaghoobi, Mohammdreza Feylizadeh
Summary: The complexity and significance of decision-making in selecting suppliers highlight the need for a systematic and transparent approach. This study developed a system dynamics model that considers social corporate responsibility (CSR) practices to help supply chain members gain competitive power and satisfy customer demands optimally.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Xin Dong, Zeeshan Ali, Tahir Mahmood, Peide Liu
Summary: This paper introduces the application of complex interval-valued q-rung orthopair fuzzy set in decision-making problems, including distance measures, Yager operational laws, and their comparison method. Several operators are developed based on CIVQROF information. Furthermore, a new technique for handling multi-attribute decision-making problems is proposed, and a practical evaluation on high blood pressure diseases is conducted to demonstrate the feasibility and worth of the approaches.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Xinming Shi, Zeeshan Ali, Tahir Mahmood, Peide Liu
Summary: In this study, Aczel-Alsina t-norm and t-conorm are extended to Interval-valued Atanassov intuitionistic fuzzy set (IVA-IFS), and the interval-valued Atanassov intuitionistic fuzzy Aczel-Alsina power averaging (IVA-IFAAPA), interval-valued Atanassov intuitionistic fuzzy Aczel-Alsina power ordered averaging (IVA-IFAAPOA), interval-valued Atanassov intuitionistic fuzzy Aczel-Alsina power geometric (IVA-IFAAPG), and interval-valued Atanassov intuitionistic fuzzy Aczel-Alsina power ordered geometric (IVA-IFAAPOG) operators are proposed. The properties of these operators are discussed, and a multi-attribute decision-making procedure is proposed to process the IVA-IF information. A practical example is used to demonstrate the effectiveness and superiority of the proposed method compared to existing operators.
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Yaru Li, Lin Li, Jing Bai, Xiaolin Chang, Yingying Yao, Peide Liu
Summary: Service function chain (SFC) based on network function virtualization (NFV) technology can handle network traffic flexibly and efficiently. However, the virtual network function (VNF) may experience software aging, which reduces the availability and reliability of SFC and even leads to service interruption. This paper proposes a semi-Markov model to capture the behaviors of each VNF in a SFC and evaluates the effectiveness of software rejuvenation technique in improving availability and reliability.
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS
(2023)
Article
Automation & Control Systems
Peide Liu, Qian Pan, Baoying Zhu
Summary: Reasonable selection of the location of temporary marine dumping areas is crucial to the high-quality development of the marine economy. This study proposes a fuzzy ELECTRE II model based on S-shaped utility function and game theory to solve the multi-attribute decision-making problem. The model considers human bounded rationality and combination weight, providing a new and effective framework for the location selection of temporary marine dumping areas.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2023)
Article
Automation & Control Systems
Xiaoming Qi, Zeeshan Ali, Tahir Mahmood, Peide Liu
Summary: In this paper, a novel concept of complex interval-valued q-rung orthopair linguistic (CIVq-ROL) information is proposed by integrating complex interval-valued q-rung orthopair fuzzy (CIVq-ROF) information and linguistic set (LS). New operational laws of the CIVq-ROF information based on algebraic t-norm and t-conorm are developed. The proposed CIVq-ROL operators, including CIVq-ROL Heronian mean (CIVq-ROLHM), CIVq-ROL weighted HM (CIVq-ROLWHM), CIVq-ROL geometric HM (CIVq-ROLGHM), and CIVq-ROL weighted geometric HM (CIVq-ROLWGHM) operators, are investigated. A MADM procedure for evaluating businesses is developed based on the proposed operators. Various examples and a comparative analysis are provided to demonstrate the application and advantages of the proposed approaches.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2023)
Article
Automation & Control Systems
Peide Liu, Zeeshan Ali, Tahir Mahmood, Yushui Geng
Summary: The major contribution of this study is to propose aggregation operators based on Aczel-Alsina t-norms for handling fuzzy values in complex intuitionistic fuzzy sets, and the superiority and effectiveness of the proposed approaches are demonstrated through examples.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Xiaoming Wu, Zeeshan Ali, Tahir Mahmood, Peide Liu
Summary: This manuscript develops Yager operational laws based on CQ-ROF information and Yager t-norm and t-conorm. The power, averaging, and geometric aggregation operators play a crucial role in aggregating CQ-ROF values. The proposed CQ-ROF power Yager averaging, CQ-ROF power Yager ordered averaging, CQ-ROF power Yager geometric, and CQ-ROF power Yager ordered geometric operators are modifications of existing operators based on various types of fuzzy sets.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Transportation
Peide Liu, Qian Pan, Baoying Zhu
Summary: This paper aims to examine the dynamic evolution of high-quality development (HQD) in China's coastal ports from the perspective of green total factor productivity (GTFP). Undesirable outputs are calculated using defined standards, and an integrated environmental dumping indicator is calculated using a combination weight calculation model based on game theory. The GTFP growth of ports is measured using a super-efficiency DEA-GML index model based on directional distance function (DDF), and the dynamic evolution is explored using kernel density estimation. The findings reveal continued improvement in GTFP growth of coastal ports, but also highlight issues with ineffective outputs from port construction inputs and a tendency towards stability within coastal ports. Targeted policy implications are provided to promote HQD of ports.
MARITIME POLICY & MANAGEMENT
(2023)
Article
Computer Science, Artificial Intelligence
Sukhwinder Singh Rawat, Peide Komal, Peide Liu, Zeljko Stevic, Tapan Senapati, Sarbast Moslem
Summary: This paper introduces a new approach for multi-attribute group decision-making, where attributes are placed into independent groups through partitioning. The proposed approach integrates the attributes from different groups while preserving the relationships within each group. The results show that applying attribute partitioning in the approach reduces the adverse impact of irrelevant attributes and leads to more feasible and reliable outcomes.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Peide Liu, Mengjiao Shen, Yushui Geng
Summary: This article presents an improved failure mode and effects analysis (FMEA) method that combines the Weighted Aggregates Sum Product Assessment (WASPAS) method and weight determination method to address the drawbacks of the traditional FMEA method. The proposed method utilizes probabilistic double hierarchy linguistic term sets (PDHLTSs) to provide linguistic information and constructs a risk evaluation model. The method overcomes the limitations of the traditional FMEA method and incorporates expert weights and a multi-attribute decision-making method to rank risk failures. The proposed method is applied to marine risk assessment and demonstrates its superiority through sensitivity analysis and comparison with existing methods.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Peng Wang, Ran Dang, Peide Liu, Dragan Pamucar
Summary: This paper proposes a decision-making method based on probabilistic linguistic preference relation (PLPR) and introduces an adjustment mechanism using attitudes and emotions to handle unknown information and improve consistency. By defining different concepts and distance measures, this method can more accurately reflect the decision-maker's preference information.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Peide Liu, Qaisar Khan, Ayesha Jamil, Ijaz Ul Haq, Waseem Sikandar, Fawad Hussain
Summary: This study proposes a new approach to deal with multi-attribute group decision-making problems by using T-Spherical Fuzzy Set to accommodate greater uncertainty. By introducing new aggregation operators, the influence of uncomfortable data can be eliminated and the relationships between input arguments can be considered simultaneously.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Peng Wang, Yingxin Fu, Peide Liu, Baoying Zhu, Fubin Wang, Dragan Pamucar
Summary: This study explores the ecological governance of the Yellow River and proposes a multi-perspective evaluation method. By using BWM and IGR methods to calculate the weights of the indicators and combining multiple methods for comprehensive evaluation, policy recommendations for the ecological governance of the Yellow River Basin are obtained.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)