Article
Computer Science, Artificial Intelligence
Rajkumar Verma, Eduardo Alvarez-Miranda
Summary: This paper introduces the flexibility and efficiency of 2-tuple linguistic Pythagorean fuzzy values (2TLPFVs) in representing fuzzy linguistic information in complex real-world situations. It presents a new score value function for 2TLPFVs and discusses its major properties. Additionally, two new aggregation operators (AOs) are proposed to aggregate 2TLPFVs based on novel operational laws. The article also discusses entropy and divergence measures in the 2TLPFV information environment, and constructs a new multiple attribute group decision-making method for solving group decision-making problems.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Environmental Sciences
Fatemeh Alamroshan, Mahyar La'li, Mohsen Yahyaei
Summary: The research addresses the supplier selection problem in the supply chain management area, focusing on green and agile aspects. A hybrid fuzzy decision-making approach is developed using FDEMATEL, FBWM, FANP, and FVIKOR methods, with a case study in the medical devices industry. The study finds that price and greenness are crucial factors in supplier selection, along with material costs, environmental performance evaluation, manufacture flexibility, service level, and system reliability.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Environmental Sciences
Alireza Fallahpour, Sina Nayeri, Mohammad Sheikhalishahi, Kuan Yew Wong, Guangdong Tian, Amir Mohammad Fathollahi-Fard
Summary: This study introduces a fuzzy decision framework to investigate the sustainable-resilient supplier selection problem in the palm oil industry in Malaysia. A hyper-hybrid model is developed using FDEMATEL, FBWM, FANP, and FIS methods. The findings of the study indicate high performance of the proposed framework in identifying important criteria for supplier selection.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
Article
Computer Science, Theory & Methods
Xingli Wu, Huchang Liao
Summary: Establishing long-term cooperative relationships with reliable suppliers of green agricultural products is essential to the sustainable development of fresh supermarkets. This paper introduces a geometric linguistic scale to capture the mathematical implications of linguistic evaluations and link them with decision-makers' psychology. Aggregation methods based on the geometric linguistic scale are developed to handle decision matrices with direct linguistic evaluations, full pairwise comparisons, and partial pairwise comparisons, respectively.
FUZZY SETS AND SYSTEMS
(2023)
Article
Environmental Sciences
Qiushuang Wei, Chao Zhou
Summary: This paper provides insights into electric vehicle supplier selection from the perspective of government agencies and public bodies using an integrated multi-criteria decision-making framework. Through a case study and analysis, it determines the importance of criteria such as bad environmental record, cost, quality, service, and environmental initiatives in electric vehicle supplier selection.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Tai-Wu Chang, Chun-Jui Pai, Huai-Wei Lo, Shu-Kung Hu
Summary: This paper proposes a sustainable supplier evaluation and selection framework for electronics manufacturing, including four dimensions of economic, social, environmental, and institutional sustainability. By integrating a modified method that combines attribute ratio analysis and the preference ranking organization method, an improved hybrid decision-making analysis model is developed.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Chiranjibe Jana, Harish Garg, Madhumangal Pal, Biswajit Sarkar, Guiwu Wei
Summary: This article introduces logarithmic operations on bipolar fuzzy numbers and presents new operators based on these operations. It also develops a multi-attribute group decision-making methodology model using logarithm bipolar fuzzy operators. The proposed model is validated using MABAC methods and applied to solve supply chain management problems. The results show that the proposed model is accurate, effective, and reliable.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Thermodynamics
M. Alipour, R. Hafezi, Pratibha Rani, Mehdi Hafezi, Abbas Mardani
Summary: This paper presents an integrated approach using entropy, SWARA, and COPRAS methods for FCH supplier selection, overcoming the shortcomings of traditional methods by combining objective and subjective weights, and using Pythagorean fuzzy set to handle uncertain information.
Article
Computer Science, Interdisciplinary Applications
Liguo Fei, Yuqiang Feng, Hongli Wang
Summary: The paper introduces a novel human-centric heterogeneous multi-attribute decision-making approach based on Dempster-Shafer theory, which can better adapt to the diverse backgrounds and preferences of decision-makers. The approach is built on subjective attitudes of decision-makers, incorporating human cognitive aspects.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Automation & Control Systems
Peide Liu, Hui Gao
Summary: This paper proposes a green supplier selection method based on multi-criteria decision-making, which combines the advantages of prioritized aggregation, Choquet integral, Bonferroni mean, and interval type-2 fuzzy set, allowing for the consideration of interactions, interrelationships, and prioritizations over the criteria simultaneously.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2021)
Article
Green & Sustainable Science & Technology
Mohit Verma, Prabhat Ranjan Prem, Peijia Ren, Huchang Liao, Zeshui Xu
Summary: This paper presents a methodology for green supplier selection that considers both qualitative and quantitative criteria, using thermodynamic features such as energy, exergy and entropy. The main advantage of this method is that it takes into account the quality of ratings assigned by experts. It is not only effective in green supplier selection, but also useful for resource allocation and scheduling of supplier training programs.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2022)
Article
Mathematics
Yanru Zhong, Zhengshuai Lu, Yiyuan Li, Yuchu Qin, Meifa Huang
Summary: In this paper, an improved interval-valued hesitant fuzzy weighted geometric (IIVHFWG) operator is proposed for multi-criterion decision-making. This operator overcomes the limitations of existing operators, which are prone to being influenced by extreme values. A new method to solve multi-criterion decision-making problems with interval-valued hesitant fuzzy elements is presented based on the proposed IIVHFWG operator. Numerical examples and comparisons demonstrate the effectiveness and advantages of this method.
Article
Computer Science, Artificial Intelligence
Wan Syahimi Afiq Wan Ahlim, Nor Hanimah Kamis, Sharifah Aniza Sayed Ahmad, Francisco Chiclana
Summary: Trust relation and similarity are integrated in constructing a similarity-trust network for consensus group decision-making. Experts are grouped using hierarchical clustering, and their similarity-trust centrality index is determined using centrality concept for deriving a consensus solution. The study shows promising results with potential application in certain consensus group decision-making problems.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Li Yan, Zheng Pei
Summary: The notable characteristic of large-scale linguistic decision-making problems is the abundance of decision makers using fuzzy linguistic representation models, leading to different linguistic assessments. A novel linguistic decision-making method based on the voting model is proposed to handle multi-linguistic assessments in large-scale linguistic decision-making problems.
Article
Computer Science, Information Systems
Abrar Hussain, Kifayat Ullah, Tapan Tehreem, Tapan Senapati, Sarbast Moslem
Summary: In this article, the concept of Complex Picture Fuzzy Set (CPFS) is introduced, and new methodologies and tools are developed using CPF information to address challenges in the supply chain. Additionally, prioritized aggregation operators (AOs) are proposed to deal with the impact of uncertainty and imprecision. The flexibility and consistency of these approaches are demonstrated through a case study and by comparing results with existing methods in the literature review.
Article
Computer Science, Interdisciplinary Applications
Dejian Yu, Libo Sheng
Article
Computer Science, Artificial Intelligence
Dejian Yu, Zeshui Xu, Witold Pedrycz
APPLIED SOFT COMPUTING
(2020)
Article
Green & Sustainable Science & Technology
Dejian Yu, Libo Sheng
Summary: This paper systematically investigates the knowledge base and knowledge diffusion paths of the closed-loop supply chain (CLSC) domain from both static and dynamic perspectives, utilizing bibliometrics to analyze characteristics of publications, authors, institutions, countries/territories and journals. The study identifies key players and trends in CLSC research, highlighting important authors and institutions, as well as the shift towards green and sustainable CLSC practices in recent years.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Computer Science, Interdisciplinary Applications
Dejian Yu, Zhaoping Yan
Summary: This study explores knowledge diffusion and thematic evolution in the field of BWE through main path analysis and science mapping analysis, identifying that most studies focus on investigating the causes and mitigation strategies of BWE. Seven main thematic areas in BWE research have been identified through analysis of the literature.
Article
Automation & Control Systems
Dejian Yu, Libo Sheng, Zeshui Xu
Summary: This paper investigates the hot topics and trends in the hesitant fuzzy domain based on 1070 retrieved papers, revealing that decision-making and extensions of HFS are becoming increasingly prominent. Main path analysis shows that the application of hesitant fuzzy theory in the decision-making field remains the most popular research direction.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2022)
Article
Computer Science, Interdisciplinary Applications
Dejian Yu, Zhaoping Yan
Summary: This article introduces a research front identification method that combines machine learning and main path analysis to quickly and accurately identify the hotspots and development trends in a specific field. By analyzing papers and patents, this method integrates the advantages of citation analysis and semantic analysis to identify research front from the perspective of science-technology linkage.
Article
Economics
Dejian Yu, Libo Sheng, Shunshun Shi
Summary: This research offers a comprehensive examination of the Journal of Forecasting (JoF) from two perspectives. It analyzes the number of publications, citations, and content of 1403 indexed articles from 1982 to 2019, as well as the knowledge flow between JoF and other categories. The research presents a novel and comprehensive framework for journal evaluation, providing insights into the historical patterns, current developments, and future dynamics of JoF.
JOURNAL OF FORECASTING
(2023)
Article
Computer Science, Artificial Intelligence
Dejian Yu, Tianxing Pan, Zeshui Xu, Ronald R. R. Yager
Summary: In recent years, the OWA operator has received increasing attention in the academic community. Growth curve analysis, commonly used in ecosystem studies, suggests that this trend will continue. However, previous literature has not provided a comprehensive overview of the field's development and evolution. This study employed classic main path analysis and its variations on a citation network of 1474 papers to uncover the development trajectories and research topics of OWA. The findings reveal the pervasive presence of weight generation and operator generalization in the OWA domain, the dynamic and multi-period nature of the multiple criteria decision-making process, and the incorporation of theories like social network theory and expanded applications of the OWA operator.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Computer Science, Information Systems
Dejian Yu, Zhaoping Yan
Summary: This article evaluates 1446 articles related to the PageRank (PR) algorithm and explores the overall development trend of the PR domain through main path analysis (MPA). By identifying leading papers through two main paths, the backbone of the PR field is outlined. Four main subareas are investigated, including accelerating PR computation, comprehensive applications of PR, research on academic impact assessment, and age preference in network evolution. The article discusses research findings and future directions of the PR field, providing insight into the knowledge evolution of the PR field over the past two decades through MPA.
JOURNAL OF INFORMATION SCIENCE
(2023)
Article
Industrial Relations & Labor
Dejian Yu, Bo Xiang
Summary: The purpose of this study is to comprehensively review the field of human resource management (HRM) and employment relations (ERs) and explore its knowledge map, knowledge evolution trends and paths, and paradigm shifts. The study applies the Structural Topic Model combined with Word2vec to analyze 23,786 papers from 29 important journals in the field from 1990 to 2021. The findings include the identification of sixteen research topics, the mapping of topic popularity trends over time, and the exploration of research topic evolution from a semantic perspective.
INTERNATIONAL JOURNAL OF MANPOWER
(2023)
Article
Computer Science, Interdisciplinary Applications
Dejian Yu, Anran Fang
Summary: This paper provides a systematic review of the knowledge trajectory and structure of the supply chain integration (SCI) field. The study identifies three distinct knowledge development trajectories and reveals three critical subfields. It highlights the lack of unified conclusions regarding the definition, content, and dimensions of SCI, as well as the long-standing research elements of influencing factors and performance consequences. The study also emphasizes the importance of building theoretical models, integrated systems, and applying blockchain technology to improve SCI.
JOURNAL OF ENTERPRISE INFORMATION MANAGEMENT
(2023)
Article
Computer Science, Artificial Intelligence
Dejian Yu, Bo Xiang
Summary: Artificial Intelligence (AI) has significantly impacted various aspects of social life. This study analyzed 177,204 documents published from 1990 to 2021 in AI research and used the LDA model to extract 40 topics from the abstracts. The study identified 7 subfields in the AI field and aggregated the results to understand research characteristics from different perspectives. These findings are valuable for researchers and institutions in selecting research directions and for newcomers to comprehend the dynamics of the field.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Dejian Yu, Anran Fang, Zeshui Xu
Summary: This study utilizes topic models to extract ten crucial scientific topics from a large dataset of fuzzy research articles and thoroughly discusses their characteristics and trends over time at both journal and country/region levels. The findings provide valuable insights into the distribution and future development of fuzzy research topics.
INFORMATION SCIENCES
(2023)
Article
Computer Science, Information Systems
Dejian Yu, Yan Liu, Zeshui Xu
Summary: Since the proposal of the preference ranking organization method for enrichment evaluations (PROMETHEE), numerous papers have been published in WoS-indexed journals, covering applications across various fields. This paper aims to present the dynamic evolution of knowledge regarding cognitive structure and transmission trajectories from a longitudinal perspective. By retrieving 1351 documents from 1982 to 2021, the interrelationships and characteristics of essential themes, as well as key thematic areas formed through their evolution, were explored. The most critical milestone documents were identified and presented chronologically, serving as an entry point for newcomers in this domain.
INFORMATION SCIENCES
(2023)
Article
Management
Dejian Yu, Tianxing Pan
Summary: Blockchain technology has been increasingly utilized in various fields in recent years, yet there is a lack of research reports on innovation paths from a patent perspective. This paper conducted main path analysis on a total of 14,560 patents to provide an overview of blockchain development and identify key patents, structural backbones, and development trajectories. This analysis serves as a reference for understanding the current state of blockchain technology and informing future research directions.
TECHNOLOGY ANALYSIS & STRATEGIC MANAGEMENT
(2021)
