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A variety of fuzzy multiple criteria decision making (MCDM) models have been proposed to solve complicated decision-making problems. Many applications have been achieved, especially in the field of civil engineering. To analyze the developments about the fuzzy MCDM methods and their applications in civil engineering in recent years and further explore the future research directions, this study conducts a state of the art survey in which 52 journal papers focusing on the applications of fuzzy MCDM models in civil engineering from 2016 to 2020 are reviewed. We respectively classify these articles according to research problems and research methods. Through the literature review, we get findings in terms of the most concerned decision-making problem, the most widely-used evaluation criterion and the most popular fuzzy MCDM model. Furthermore, we present four aspects of research challenges and corresponding future research directions in the field of civil engineering, which may be helpful for researchers and practitioners to further investigate.
Zhi Wen; Huchang Liao; Edmundas Kazimieras Zavadskas; Jurgita Antuchevičienė. APPLICATIONS OF FUZZY MULTIPLE CRITERIA DECISION MAKING METHODS IN CIVIL ENGINEERING: A STATE-OF-THE-ART SURVEY. JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT 2021, 27, 358 -371.
AMA StyleZhi Wen, Huchang Liao, Edmundas Kazimieras Zavadskas, Jurgita Antuchevičienė. APPLICATIONS OF FUZZY MULTIPLE CRITERIA DECISION MAKING METHODS IN CIVIL ENGINEERING: A STATE-OF-THE-ART SURVEY. JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT. 2021; 27 (6):358-371.
Chicago/Turabian StyleZhi Wen; Huchang Liao; Edmundas Kazimieras Zavadskas; Jurgita Antuchevičienė. 2021. "APPLICATIONS OF FUZZY MULTIPLE CRITERIA DECISION MAKING METHODS IN CIVIL ENGINEERING: A STATE-OF-THE-ART SURVEY." JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT 27, no. 6: 358-371.
Developing low-carbon tourism can not only improve the ecological environment, but also promote the development of economy in China. To select a desirable low-carbon tourism destination, we need to consider multiple conflicting and incommensurate criteria, simultaneously. However, traditional decision-making methods such as analytical hierarchy process and Delphi fail to model the complex cognition of decision makers. In this regard, this article proposes a novel multi-criteria decision making method called the thermodynamic feature-based method to aid decision makers to select the optional low-carbon tourism destination. The q-rung orthopair fuzzy set (q-ROFS), as a recently proposed information representation model, is used to express the imprecise information of decision makers. We first introduce new distance measures of q-ROFSs and investigate their desirable properties in detail. Afterwards, a thermodynamic feature-based method is developed from the aspects of energy, exergy and entropy of alternatives integrating both quantitative and qualitative decision information. Finally, a case study concerning the selection of low-carbon tourism destination is given to illustrate the applicability and superiority of the proposed method.
Cheng Zhang; Huchang Liao; Li Luo; Zeshui Xu. Low-carbon tourism destination selection by a thermodynamic feature-based method. Journal of the Operational Research Society 2021, 1 -16.
AMA StyleCheng Zhang, Huchang Liao, Li Luo, Zeshui Xu. Low-carbon tourism destination selection by a thermodynamic feature-based method. Journal of the Operational Research Society. 2021; ():1-16.
Chicago/Turabian StyleCheng Zhang; Huchang Liao; Li Luo; Zeshui Xu. 2021. "Low-carbon tourism destination selection by a thermodynamic feature-based method." Journal of the Operational Research Society , no. : 1-16.
In a group decision-making process, contradictory pairwise comparisons may exist in individual preferences or the group preferences even though the consensus level is reached. To avoid such a contradictory phenomenon, this study presents an approximate transitivity-based consistency threshold for reciprocal preference relations to ensure the reliability of the ranking of alternatives with reciprocal preference relations in group decision making. The natural inconsistency or intransitivity of reciprocal preference relations is analyzed and verified by numerical experiments. Then, using the results of numerical experiments, approximate transitivity-based consistency thresholds are introduced based on the objectives of minimising the Type I error, Type II error and total error in statistics. Moreover, a transitivity checking process regarding individual reciprocal preference relations and group reciprocal preference relations is incorporated in the group decision-making process. A transitivity-checking integrated group decision-making model is given for application. An example about the station selection for high-speed railway line is provided to show the necessity of the approximate transitivity-based consistency threshold in checking the transitivity of reciprocal preference relations for group decision making.
Xiaomei Mi; Huchang Liao; Xiao-Jun Zeng. Transitivity and approximate consistency threshold determination for reciprocal preference relations in group decision making. Journal of the Operational Research Society 2021, 1 -18.
AMA StyleXiaomei Mi, Huchang Liao, Xiao-Jun Zeng. Transitivity and approximate consistency threshold determination for reciprocal preference relations in group decision making. Journal of the Operational Research Society. 2021; ():1-18.
Chicago/Turabian StyleXiaomei Mi; Huchang Liao; Xiao-Jun Zeng. 2021. "Transitivity and approximate consistency threshold determination for reciprocal preference relations in group decision making." Journal of the Operational Research Society , no. : 1-18.
With the changes of lifestyle and environment of people, the incidence rate of lung cancer has increased year by year, and lung cancer has become one of the most malignant tumors that threaten the health of people. Within this context, choosing appropriate anti-lung cancer drugs is of great significance for the treatment of lung cancer patients. To improve the accuracy of anti-lung cancer drug selection, it is necessary to invite many experts to participate in the evaluation process, and such a selection process can be regarded as a large-scale group decision-making problem. In existing group decision-making models, there are two hypotheses: one assumed that all experts are independent, while the other assumed that experts have certain relationships. However, in practical decision-making problems involving both internal and external experts, it is common that only some experts have mutual relationships. To address this issue, this paper proposes a large-scale group decision-making model considering the trust relationship between a set of experts. We divide experts into internal experts and external experts. The internal experts are supposed to be not independent of each other due to trust relationships, and we analyze the relationships between internal experts through the DEMATEL method. The external experts are supposed to be independent of each other. Considering the non-cooperative behaviors of experts, we provide a confidence-based adaptive consensus reaching mechanism for internal experts and a delegation-based adaptive consensus reaching mechanism for external experts. The two expert panels reach consensus through their separate consensus reaching mechanisms, and the moderator determines the optimal alternative by combining the final opinions of the two expert panels. Finally, an illustrative example about the selection of anti-non-small cell lung cancer drugs is presented to show the validity and practicality of the proposed model.
Xiaofang Li; Huchang Liao. A group decision making method to manage internal and external experts with an application to anti-lung cancer drug selection. Expert Systems with Applications 2021, 183, 115379 .
AMA StyleXiaofang Li, Huchang Liao. A group decision making method to manage internal and external experts with an application to anti-lung cancer drug selection. Expert Systems with Applications. 2021; 183 ():115379.
Chicago/Turabian StyleXiaofang Li; Huchang Liao. 2021. "A group decision making method to manage internal and external experts with an application to anti-lung cancer drug selection." Expert Systems with Applications 183, no. : 115379.
Choosing a good food supply chain is helpful for realizing the coordination of economic benefits and environmental optimization, so as to promote the sustainable development of the society. To solve such a problem, we need to ensure the accuracy of the original information and the validity of the aggregated information. However, experts may not be able to give professional evaluations in some aspects, and a simple ranking of alternatives cannot accurately reflect the relations between alternatives. To solve these problems, this paper proposes a comprehensive method integrating the social participatory allocation network (SPAN) and ORESTE methods under the q-rung orthopair fuzzy environment. To better deal with the imprecise and uncertain information, the q-rung orthopair fuzzy set is adopted in this study to represent decision-makers’ opinions. The delegate mechanism of the SPAN method is introduced to calculate the weights of experts, which make the assessments of alternatives credible. The ORESTE method is used to explore the relations between alternatives in detail. The preference function is used to deal with the case where the data is not ordinal. Finally, a case study concerning the selection of sustainable food supply chains is presented to verify the applicability of the proposed method.
Yilu Long; Huchang Liao. A social participatory allocation network method with partial relations of alternatives and its application in sustainable food supply chain selection. Applied Soft Computing 2021, 109, 107550 .
AMA StyleYilu Long, Huchang Liao. A social participatory allocation network method with partial relations of alternatives and its application in sustainable food supply chain selection. Applied Soft Computing. 2021; 109 ():107550.
Chicago/Turabian StyleYilu Long; Huchang Liao. 2021. "A social participatory allocation network method with partial relations of alternatives and its application in sustainable food supply chain selection." Applied Soft Computing 109, no. : 107550.
Online reviews play an important role for the purchasing decision of customers. One challenge is that different reviewers have different judgment benchmarks when making online reviews, which can mislead purchasing decisions. Specifically, the same star rating may correspond to different levels of sentiment for different reviewers because of the explicit preference differences in individuals. This study explores the personal judgment benchmarks through a preference learning process. Considering the nonlinear cognition of reviewers, we propose a marginal value function with smooth shapes and clear parameters to model the scores of online reviews. A mathematical programming model is established to predict the specific marginal value function for each reviewer. Two kinds of performance accurateness are defined to measure the performance of the learning model. We evaluate two empirical data sets extracted from TripAdvisor.com to deepen the understanding of personal judgment benchmarks. A simulation study is conducted to validate the proposed model. The results have important theoretical and practical implications for purchasing decisions based on online reviews.
Xingli Wu; Huchang Liao. Learning judgment benchmarks of customers from online reviews. OR Spectrum 2021, 1 -33.
AMA StyleXingli Wu, Huchang Liao. Learning judgment benchmarks of customers from online reviews. OR Spectrum. 2021; ():1-33.
Chicago/Turabian StyleXingli Wu; Huchang Liao. 2021. "Learning judgment benchmarks of customers from online reviews." OR Spectrum , no. : 1-33.
With the increasing complexity of processes and products, and because of the multi-disciplinary and cross-functional nature, a failure mode and effect analysis (FMEA) practice may be implemented in a distributed setting with a large group of FMEA members. In this study, we introduce a large group decision making model for FMEA considering social relationships of FMEA members. Firstly, a group structure detection method is used to reduce the dimension of the large group, which can find a core-periphery structure and a community structure from a meso-scale perspective. Then, a delegation mechanism is introduced to allocate opinions of periphery FMEA members into those of core FMEA members. Next, we propose a fairness-oriented consensus approach considering a fair distribution of changes in the consensus reaching process. An illustrative example regarding photovoltaic systems is provided to demonstrate the applicability and effectiveness of our proposed model. The key and novel contribution of our paper is to explore how to manage the structure characteristic for FMEA groups under the social network setting. We provide an insight of efficient decision making for complex reliability engineering problems.
Ming Tang; Huchang Liao. Failure mode and effect analysis considering the fairness-oriented consensus of a large group with core-periphery structure. Reliability Engineering & System Safety 2021, 215, 107821 .
AMA StyleMing Tang, Huchang Liao. Failure mode and effect analysis considering the fairness-oriented consensus of a large group with core-periphery structure. Reliability Engineering & System Safety. 2021; 215 ():107821.
Chicago/Turabian StyleMing Tang; Huchang Liao. 2021. "Failure mode and effect analysis considering the fairness-oriented consensus of a large group with core-periphery structure." Reliability Engineering & System Safety 215, no. : 107821.
Many group decision making (GDM) models enable experts to use only one preference information representation form. It is natural to allow experts to express preferences in various formats considering the heterogeneity of experts. In this case, how to reach the consensus of a group from heterogeneous preference information is an attractive research issue. This study proposes a consensus reaching process for large-scale GDM with heterogeneous preference information. First, we review various preference formats including preference orderings, numerical assessments, interval-valued assessments, and linguistic assessments. To facilitate the heterogeneous information aggregation, we classify experts into subgroups according to their preference types rather than the similarities of preference values, and then aggregate the homogeneous preference values in each subgroup. The subgroup priorities derived by homogeneous methods are then aggregated into global priorities. An ordinal consensus measuring process based on individual orderings is introduced. To reach the ordinal consensus, optimization models are constructed to ensure each subgroup's preferences equivalent to the global preferences, and the recommended ranges and strength of preference modification are given to experts. Finally, the proposed method is validated by an illustrative example about blockchain platform selection.
Zheng Wu; Huchang Liao. A consensus reaching process for large‐scale group decision making with heterogeneous preference information. International Journal of Intelligent Systems 2021, 36, 4560 -4591.
AMA StyleZheng Wu, Huchang Liao. A consensus reaching process for large‐scale group decision making with heterogeneous preference information. International Journal of Intelligent Systems. 2021; 36 (9):4560-4591.
Chicago/Turabian StyleZheng Wu; Huchang Liao. 2021. "A consensus reaching process for large‐scale group decision making with heterogeneous preference information." International Journal of Intelligent Systems 36, no. 9: 4560-4591.
Due to the personalized and diversified expression habits, the evaluation information in multiple criteria decision-making (MCDM) problems, especially those with multiple experts, may appear in heterogeneous forms. Converting heterogeneous expressions to a single representation would lead to information loss. To solve this challenge, this article aims to address the MCDM problems with heterogeneous linguistic expressions by unifying the operations of heterogeneous linguistic representations. To do so, we propose to use expectation values and entropy measures to describe the meaning of linguistic evaluation information. The expectation functions of ten kinds of linguistic representations are respectively defined based on the semantics of linguistic terms. The entropy measures of these representations are developed to reflect the inherent uncertainty of evaluations. Afterward, a computation model for heterogeneous linguistic representations is presented based on their expectation values and entropy. On this basis, an MCDM framework with personalized heterogeneous linguistic information is constructed. A numerical example about selecting the best green logistics for a business-to-customer e-commerce enterprise shows the advantages of the proposed method in modeling personalized linguistic evaluations and retaining uncertain information in the computation process.
Xingli Wu; Huchang Liao; Benjamin Lev; Edmundas Kazimieras Zavadskas. A Multiple Criteria Decision-Making Method With Heterogeneous Linguistic Expressions. IEEE Transactions on Engineering Management 2021, PP, 1 -14.
AMA StyleXingli Wu, Huchang Liao, Benjamin Lev, Edmundas Kazimieras Zavadskas. A Multiple Criteria Decision-Making Method With Heterogeneous Linguistic Expressions. IEEE Transactions on Engineering Management. 2021; PP (99):1-14.
Chicago/Turabian StyleXingli Wu; Huchang Liao; Benjamin Lev; Edmundas Kazimieras Zavadskas. 2021. "A Multiple Criteria Decision-Making Method With Heterogeneous Linguistic Expressions." IEEE Transactions on Engineering Management PP, no. 99: 1-14.
Game theory establishes mathematical models of strategic interactions among rational decision-makers. In many situations, the crisp values of payoffs are difficult to obtain while the probabilistic linguistic information is easy to collect. However, the existing research on matrix game did not consider the probabilistic linguistic information. To bridge this gap, this study takes the probabilistic linguistic information as the input of a two-person and zero-sum matrix game, and addresses the vague information by triangular membership functions. Such a two-person and zero-sum matrix game with probabilistic linguistic information is a useful technique for multiple criteria analysis. In addition, it outputs the same form of information as the inputs to increase the interpretability compared with other uncertain matrix games. An illustrative example about the forest management is provided to show the validity and advantages of the two-person and zero-sum matrix game with probabilistic linguistic information.
Xiaomei Mi; Huchang Liao; Xiao-Jun Zeng; Zeshui Xu. The two-person and zero-sum matrix game with probabilistic linguistic information. Information Sciences 2021, 570, 487 -499.
AMA StyleXiaomei Mi, Huchang Liao, Xiao-Jun Zeng, Zeshui Xu. The two-person and zero-sum matrix game with probabilistic linguistic information. Information Sciences. 2021; 570 ():487-499.
Chicago/Turabian StyleXiaomei Mi; Huchang Liao; Xiao-Jun Zeng; Zeshui Xu. 2021. "The two-person and zero-sum matrix game with probabilistic linguistic information." Information Sciences 570, no. : 487-499.
The even swaps method considering the trade-offs between criteria is an effective multiple criteria decision making (MCDM) method; nevertheless, when implementing it, decision makers are subjected to heavy psychological burdens. The prospect theory can model the psychological characteristics of decision makers to relieve the psychological burdens of decision makers. Thus, it is effective to incorporate the prospect theory into the even swaps method so as to lighten the psychological burdens of decision makers in the even swaps method. Given that the HFLTS is a useful tool to express complex and complete evaluation information, this study aims to propose an even swaps method based on the prospect theory with hesitant fuzzy linguistic term sets (HFLTSs). To catch this goal, in the even swaps method, the value function of the prospect theory is used to measure the utility changes in the trade-offs between criteria. Then, the swapped values used to rank alternatives under the measuring stick criterion are calculated based on the operations of HFLTSs. A case study about the selection of emergency logistics plans under the COVID-19 pandemic outbreak demonstrates the feasibility of the proposed method. The sensitivity analysis and comparative analysis illustrate the reliability and stability of the proposed method.
Rui Qin; Huchang Liao; Lisheng Jiang. An enhanced even swaps method based on prospect theory with hesitant fuzzy linguistic information and its application to the selection of emergency logistics plans under the COVID-19 pandemic outbreak. Journal of the Operational Research Society 2021, 1 -13.
AMA StyleRui Qin, Huchang Liao, Lisheng Jiang. An enhanced even swaps method based on prospect theory with hesitant fuzzy linguistic information and its application to the selection of emergency logistics plans under the COVID-19 pandemic outbreak. Journal of the Operational Research Society. 2021; ():1-13.
Chicago/Turabian StyleRui Qin; Huchang Liao; Lisheng Jiang. 2021. "An enhanced even swaps method based on prospect theory with hesitant fuzzy linguistic information and its application to the selection of emergency logistics plans under the COVID-19 pandemic outbreak." Journal of the Operational Research Society , no. : 1-13.
Online reviews have become an increasingly popular information source in consumer’s decision making process. To help consumers make informed decisions, how to select products through online reviews is a valuable research topic. This work deals with a personized product selection problem with review sentiments under probabilistic linguistic circumstances. To this end, we propose a multi-criteria decision making (MCDM) method incorporating personalized heuristic judgments in the prospect theory (PT). We focus on the role of personalized heuristic judgments on review helpfulness in the final decision outcomes. We demonstrate the consistency between the three common heuristic judgments (with respect to review valence, sentiment extremity, and aspiration levels) and the three behavioral principles of the PT. Then, the products are ranked with the probabilistic linguistic term set (PLTS) input, based on the proposed adjustable PT framework, in which the coefficients of negativity bias are derived from the consumer’s heuristic judgments. Finally, a real case on TripAdvisor.com and two simulation experiments are given to illustrate the validity of the proposed method.
Meng Zhao; Xinyuan Shen; Huchang Liao; Mingyao Cai. Selecting products through text reviews: An MCDM method incorporating personalized heuristic judgments in the prospect theory. Fuzzy Optimization and Decision Making 2021, 1 -24.
AMA StyleMeng Zhao, Xinyuan Shen, Huchang Liao, Mingyao Cai. Selecting products through text reviews: An MCDM method incorporating personalized heuristic judgments in the prospect theory. Fuzzy Optimization and Decision Making. 2021; ():1-24.
Chicago/Turabian StyleMeng Zhao; Xinyuan Shen; Huchang Liao; Mingyao Cai. 2021. "Selecting products through text reviews: An MCDM method incorporating personalized heuristic judgments in the prospect theory." Fuzzy Optimization and Decision Making , no. : 1-24.
The widespread utilization of novel technological and societal paradigms gave birth to the development large-scale group decision making. This study focuses on two issues regarding the structure of the large group. The first is about the overlapping clusters/communities (interdependent subgroups) of large-scale experts identified from the dimension reduction process. The second is regarding the situation in which internal and external experts (i.e., heterogeneous experts) exist in a large-scale group decision-making problem simultaneously. To manage the first issue, we propose to use an existing overlapping community detection method to cluster experts considering the independencies of communities. To address the second issue, a delegation mechanism is introduced to allocate the trust weights of external experts to internal experts. Furthermore, to reach a consensus for large-scale experts, a consensus measure based on two reference points (global collective preference and community preference) is given. Finally, an illustrative example regarding 5G technology investment is provided to verify the applicability of the proposed model.
Ming Tang; Huchang Liao; Hamido Fujita. Delegation Mechanism-Based Large-Scale Group Decision Making With Heterogeneous Experts and Overlapping Communities. IEEE Transactions on Systems, Man, and Cybernetics: Systems 2021, PP, 1 -14.
AMA StyleMing Tang, Huchang Liao, Hamido Fujita. Delegation Mechanism-Based Large-Scale Group Decision Making With Heterogeneous Experts and Overlapping Communities. IEEE Transactions on Systems, Man, and Cybernetics: Systems. 2021; PP (99):1-14.
Chicago/Turabian StyleMing Tang; Huchang Liao; Hamido Fujita. 2021. "Delegation Mechanism-Based Large-Scale Group Decision Making With Heterogeneous Experts and Overlapping Communities." IEEE Transactions on Systems, Man, and Cybernetics: Systems PP, no. 99: 1-14.
Every practice in supply chain management (SCM) requires decision making. However, due to the complexity of evaluated objects and the cognitive limitations of individuals, the decision information given by experts is often fuzzy, which may make it difficult to make decisions. In this regard, many scholars applied fuzzy techniques to solve decision making problems in SCM. Although there were review papers about either fuzzy methods or SCM, most of them did not use bibliometrics methods or did not consider fuzzy sets theory-based techniques comprehensively in SCM. In this paper, for the purpose of analyzing the advances of fuzzy techniques in SCM, we review 301 relevant papers from 1998 to 2020. By the analyses in terms of bibliometrics, methodologies and applications, publication trends, popular methods such as fuzzy MCDM methods, and hot applications such as supplier selection, are found. Finally, we propose future directions regarding fuzzy techniques in SCM. It is hoped that this paper would be helpful for scholars and practitioners in the field of fuzzy decision making and SCM.
Keyu Lu; Huchang Liao; Edmundas Kazimieras Zavadskas. AN OVERVIEW OF FUZZY TECHNIQUES IN SUPPLY CHAIN MANAGEMENT: BIBLIOMETRICS, METHODOLOGIES, APPLICATIONS AND FUTURE DIRECTIONS. Technological and Economic Development of Economy 2021, 27, 402 -458.
AMA StyleKeyu Lu, Huchang Liao, Edmundas Kazimieras Zavadskas. AN OVERVIEW OF FUZZY TECHNIQUES IN SUPPLY CHAIN MANAGEMENT: BIBLIOMETRICS, METHODOLOGIES, APPLICATIONS AND FUTURE DIRECTIONS. Technological and Economic Development of Economy. 2021; 27 (2):402-458.
Chicago/Turabian StyleKeyu Lu; Huchang Liao; Edmundas Kazimieras Zavadskas. 2021. "AN OVERVIEW OF FUZZY TECHNIQUES IN SUPPLY CHAIN MANAGEMENT: BIBLIOMETRICS, METHODOLOGIES, APPLICATIONS AND FUTURE DIRECTIONS." Technological and Economic Development of Economy 27, no. 2: 402-458.
Online reviews play an important role in online shopping. Previous studies on Multi-Criteria Decision Making (MCDM) based on customer reviews focused too much on sentiment words in text reviews but ignored the personalized semantics of linguistic terms. In addition, only considering the qualitative information of products/services is not enough to simulate the purchase behaviors of customers given that the customers are also concerned with quantitative parameters. To bridge these research gaps, this study models the personalized cognition of customers on both quantitative and qualitative information, and proposes an MCDM framework for online shopping. Firstly, we determine the personalized semantics of linguistic terms through the emotional consistency between star ratings and text reviews. Afterwards, we investigate the “psychological intensity” based on Weber-Fechner's law to determine the utilities of quantitative parameters. A utility-based translation method is then developed to express both quantitative parameters and text reviews as probabilistic linguistic term sets. The unified information is further aggregated to represent the performance of products/services. The applicability of the proposed method is illustrated by a case study of television selection from Amazon.com. The results demonstrate that the personalized cognition has an influence on the judgments of products/services.
Xingli Wu; Huchang Liao. Modeling personalized cognition of customers in online shopping. Omega 2021, 104, 102471 .
AMA StyleXingli Wu, Huchang Liao. Modeling personalized cognition of customers in online shopping. Omega. 2021; 104 ():102471.
Chicago/Turabian StyleXingli Wu; Huchang Liao. 2021. "Modeling personalized cognition of customers in online shopping." Omega 104, no. : 102471.
In the evolution of an emergency, Internet public opinions usually catalyze escalation and spread of the emergency, and even affect the evolution of public opinions. Therefore, how to effectively manage Internet public opinions has become urgent. As an essential part of the Internet public opinion management, assessing the heat degree of Internet public opinions is necessary. Being problem-oriented, this paper analyzes the development and evolution of Internet public opinions, and identifies the characteristics of the heat degree assessment of Internet public opinions. Taking into account the continuously changing exterior environment, the dynamic nature of Internet public opinions, and the inadequacy and uncertainty of decision-making information, assessing the heat degree of Internet public opinions is regarded as a dynamic multi-attribute decision making problem under the probabilistic linguistic environment. Thus, this paper aims to develop a dynamic decision-making framework to assess the heat degrees of Internet public opinions under the probabilistic linguistic environment. First, the probabilistic linguistic Bayesian network (PLBN) is constructed, in which the nodes denote attributes and related factors, and the hierarchical network structure shows the relationship among attributes. Then, the probability information obtained by PLBN in the form of PLTS is converted into attribute weight information. Moreover, this paper starts from the nature of PLTS, discusses PLTSs in terms of the probability distribution, and then gives the concept of the dominance degree of PLTS, based on which, a dynamic decision-making model based on the idea of prospect theory that considers DMs’ bounded rationality is developed. Finally, five emergency events happened in China are selected as a case to illustrate the proposed approach and some analyses and discussions have been carried out to verify the validity of our approach.
Yixin Zhang; Zeshui Xu; Zhinan Hao; Huchang Liao. Dynamic assessment of Internet public opinions based on the probabilistic linguistic Bayesian network and Prospect theory. Applied Soft Computing 2021, 106, 107359 .
AMA StyleYixin Zhang, Zeshui Xu, Zhinan Hao, Huchang Liao. Dynamic assessment of Internet public opinions based on the probabilistic linguistic Bayesian network and Prospect theory. Applied Soft Computing. 2021; 106 ():107359.
Chicago/Turabian StyleYixin Zhang; Zeshui Xu; Zhinan Hao; Huchang Liao. 2021. "Dynamic assessment of Internet public opinions based on the probabilistic linguistic Bayesian network and Prospect theory." Applied Soft Computing 106, no. : 107359.
Due to the importance of correlation coefficient in data analysis, researchers have shown interest in the concept of correlation coefficient for the extensions of fuzzy sets, in particular, for a recent established extension known as hesitant fuzzy set (HFS). Most of the existing correlation coefficients for fuzzy sets return the value one to reflect a perfect linear relationship between objects, but they do not give us sufficient information about the scale with that the objects are correlated. This can be regarded as a disadvantage from the decision-making viewpoint. Moreover, some of the existing correlation coefficients were undefined in the case that the two objects are the same. To overcome such drawbacks, we propose an approach for deriving the modified correlation coefficients of HFSs based on hesitancy degree and then extend the approach to that of interval-valued hesitant fuzzy sets. Furthermore, we put forward a number of new correlation coefficients for HFSs based on Jaccard’s and Dice’s similarity criteria. Then, we give a practical example to illustrate the application of the improved correlation coefficients for HFSs in medical diagnosis. However, comparing the results of the proposed correlation coefficients with those of the other existing definitions shows that the diagnosis results may be quite different, and this is due to their orientation.
B. Farhadinia; H. Liao; E. Herrera-Viedma. A modified class of correlation coefficients of hesitant fuzzy information. Soft Computing 2021, 25, 7009 -7028.
AMA StyleB. Farhadinia, H. Liao, E. Herrera-Viedma. A modified class of correlation coefficients of hesitant fuzzy information. Soft Computing. 2021; 25 (10):7009-7028.
Chicago/Turabian StyleB. Farhadinia; H. Liao; E. Herrera-Viedma. 2021. "A modified class of correlation coefficients of hesitant fuzzy information." Soft Computing 25, no. 10: 7009-7028.
With the applications of blockchain technology in various fields, the research on blockchain has attracted much attention. Different from the researches focusing on specific applications of blockchain technology in a certain field, this study devotes to capturing the attitudes of investors regarding different risk criteria in blockchain technology investment decision making. We use personalized quantifiers to extract investors’ preferences on each risk evaluation criterion. At present, the personalized quantifier that can reflect individual attitudes and behavior intentions have been fitted by various functions, but there are still limitations. In this regard, this paper introduces a cubic spline interpolation function to fit the personalized quantifier, and addresses the consistency of the personalized quantifier in the ordered weighted averaging aggregation. Moreover, we employ a qualitative information representation model called probabilistic linguistic term sets to express decision-makers' evaluations on each criterion. We give a case study to illustrate the usability of the proposed personalized quantifier in blockchain risk evaluation. The comparative analysis with other four types of personalized quantifiers shows that our proposed personalized quantifier with cubic spline interpolation has ideal geometric characteristics in terms of smooth curve and high fitting accuracy, thus having strong applicability. Further, we show that this method is relatively easy to operate.
Zhi Wen; Huchang Liao; Ali Emrouznejad. Information representation of blockchain technology: Risk evaluation of investment by personalized quantifier with cubic spline interpolation. Information Processing & Management 2021, 58, 102571 .
AMA StyleZhi Wen, Huchang Liao, Ali Emrouznejad. Information representation of blockchain technology: Risk evaluation of investment by personalized quantifier with cubic spline interpolation. Information Processing & Management. 2021; 58 (4):102571.
Chicago/Turabian StyleZhi Wen; Huchang Liao; Ali Emrouznejad. 2021. "Information representation of blockchain technology: Risk evaluation of investment by personalized quantifier with cubic spline interpolation." Information Processing & Management 58, no. 4: 102571.
With the increasing popularity of Pharmaceutical Industry 4.0, products and services provided by suppliers play a significantly important role for a pharmaceutical enterprise. To evaluate the performance of suppliers comprehensively regarding multiple criteria, it is necessary to invite inside managers from the enterprise and outside consultants with expertise to form a decision-making committee. Within this context, this study proposes a multi-attribute group decision making model for pharmaceutical supplier selection with internal and external (heterogeneous) experts. Considering the complexity of the decision-making environment, we suppose that the experts use triangular fuzzy numbers to express their imprecise information. We identify two kinds of conflicts among experts, and introduce a conflict resolution process with a feedback mechanism. In the feedback mechanism, two non-cooperative behavior management approaches are introduced corresponding to the two kinds of experts. Afterwards, an algorithm for multiple-attribute group decision making with triangular fuzzy numbers and heterogeneous experts is presented. Finally, an illustrative example about pharmaceutical supplier selection is provided to verify the feasibility of the proposed method and some managerial insights are given.
Huchang Liao; Lisi Kuang; Yuxi Liu; Ming Tang. Non-cooperative behavior management in group decision making by a conflict resolution process and its implementation for pharmaceutical supplier selection. Information Sciences 2021, 567, 131 -145.
AMA StyleHuchang Liao, Lisi Kuang, Yuxi Liu, Ming Tang. Non-cooperative behavior management in group decision making by a conflict resolution process and its implementation for pharmaceutical supplier selection. Information Sciences. 2021; 567 ():131-145.
Chicago/Turabian StyleHuchang Liao; Lisi Kuang; Yuxi Liu; Ming Tang. 2021. "Non-cooperative behavior management in group decision making by a conflict resolution process and its implementation for pharmaceutical supplier selection." Information Sciences 567, no. : 131-145.
Since more and more blockchain platforms have been utilized in diverse business applications, the blockchain platform evaluation becomes significant for clients. There are challenges regarding the blockchain platform evaluation in terms of information uncertainty, multiple types of criteria, and the correlations between criteria. This study dedicates to proposing a method to solve these problems by integrating linguistic D numbers (LDNs), double normalization-based multiple aggregation (DNMA) method, and Criteria Importance Through Inter-criteria Correlation (CRITIC) method. Firstly, a conversion rule of LDNs is introduced to enhance the comparative rule of LDNs. Then, an integrated multiple criteria decision making framework is proposed by incorporating DNMA with LDNs. This method not only can effectively capture the incomplete or uncertain decision-making information with respect to cost, benefit, and target criteria, but also can reduce the loss of decision information caused by single normalized technology. The CRITIC method is integrated in the LDN-based DNMA method to reflect the correlations between criteria in the blockchain platform evaluation process. To investigate the efficiency of the proposed method, a numerical example of blockchain platform evaluation is given. The sensitivity analysis demonstrates the robustness and stability of the developed method. The comparative analysis shows that our method can identify the potentially important criteria in the decision-making process effectively.
Han Lai; Huchang Liao. A multi-criteria decision making method based on DNMA and CRITIC with linguistic D numbers for blockchain platform evaluation. Engineering Applications of Artificial Intelligence 2021, 101, 104200 .
AMA StyleHan Lai, Huchang Liao. A multi-criteria decision making method based on DNMA and CRITIC with linguistic D numbers for blockchain platform evaluation. Engineering Applications of Artificial Intelligence. 2021; 101 ():104200.
Chicago/Turabian StyleHan Lai; Huchang Liao. 2021. "A multi-criteria decision making method based on DNMA and CRITIC with linguistic D numbers for blockchain platform evaluation." Engineering Applications of Artificial Intelligence 101, no. : 104200.