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Evaluation of the results of multi-attribute group decision-making with linguistic information

OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2012年第3期40卷 294-301页

作者： Pang, Jifang Liang, Jiye Shanxi Univ Sch Management Taiyuan 030006 Shanxi Peoples R China Shanxi Univ Inst Intelligent Informat Proc Taiyuan 030006 Shanxi Peoples R China Shanxi Univ Sch Comp & Informat Technol Taiyuan 030006 Shanxi Peoples R China

multi-attribute group decision-making (MAGDM) has received increasing attentions in both engineering and economy fields. Correspondingly, many valuable methods have been developed to solve various MAGDM problems, but relatively, very few research results focus on the evaluation of the effect of MAGDM. In this paper, based on the existing MAGDM methods with linguistic information, three key evaluation indices, consistency, closeness and uniformity, are proposed to measure the results of MAGDM from different aspects. By comparing the individual overall preference values with the collective ones, the three indices cannot only provide a reference for judging the decision-making effect of each decision maker, but also reflect the effect of group decision-making to a certain extent. The practicality and effectiveness of the proposed method are shown by two heuristic examples. Furthermore, the proposed method will be helpful for setting and adjusting the weights of both attributes and decision makers, as well as for selecting and comparing various aggregation operators and methods in dynamic or interactive group decision-making. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： multi-attribute group decision-making Linguistic information Individual overall preference values Collective overall preference values Evaluation

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A threat assessment method of group targets based on interval-valued intuitionistic fuzzy multi-attribute group decision-making

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APPLIED SOFT COMPUTING 2018年 67卷 350-369页

作者： Kong, Depeng Chang, Tianqing Wang, Quandong Sun, Haoze Dai, Wenjun Acad Army Armored Forces Dept Arms & Control Beijing 100072 Peoples R China

group target (GT) is consisted of multi-class weapons that can collaboratively work and it is a basic application unit in the information warfare. Assessing the threat of GT is required for the optimal decision of troop deployment. However, it is difficult to obtain a reasonable and effective threat assessment result of GT due to the uncertain battlefield information and different judgments from various decision makers (DMs). The study aims to investigate the multi-attribute group decision-making (MAGDM) method for solving the interval-valued intuitionistic fuzzy threat assessment problem of GTs without known attribute weights and DM's preference weights. Based on the assessment information of DMs, attribute weights are determined with the interval-valued intuitionistic fuzzy entropy. To derive the DM's preference weights objectively, we construct a nonlinear optimization model to minimize decision makers' overall decision-making conflict. Moreover, the artificial bee colony algorithm is introduced to solve the nonlinear constrained optimization problem in the optimization model. The decision information of multi-DM is aggregated by the interval-valued intuitionistic fuzzy weighted averaging operator (IVIFWA) with the DMs' preference weights. In order to describe the attribute closeness degree to the ideal solution, the decision-making judgment matrix is constructed according to the ideal solution closeness degree of each GT's attribute calculated with the cross-entropy distance. Subsequently, based on the decision-making judgment matrix, the threat degree is calculated according to the weighted average method with the attribute weights. Finally, a case of the threat assessment of group targets is provided to illustrate the implementation process and applicability of the method proposed in this paper. (C) 2018 Elsevier B.V. All rights reserved.

关键词： group target Intuitionistic fuzzy entropy Interval-valued intuitionistic fuzzy set multi-attribute group decision-making Threat assessment

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A Two-Stage multi-attribute group decision-making Model Based on Regret Theory and Three-Way decision Method with R-Numbers

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INTERNATIONAL JOURNAL OF FUZZY SYSTEMS 2024年 1-37页

作者： Cheng, Rui Fan, Jianping Wu, Meiqin Chen, Ruixin Shanxi Univ Sch Econ & Management Taiyuan 030006 Peoples R China

Two-stage decision making is commonly observed in practical multi-attribute risk decision making. decision makers face unpredictable risk forecasts and must engage in multi-attribute decision making while being limited by external circumstances in both the preceding and subsequent stages. The outcomes of the initial phase of decision making influence the level of risk that arises in the subsequent phase and directly affect the outcomes of the subsequent phase. The R-numbers two-stage multi-attribute group decision-making (R-TSMAGDM) approach is based on the advantages of R-numbers in effectively representing risk. An expert weight determination model is created using distance measures of R-numbers, inspired by the ideas of TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). The R-numbers weighted Muirhead mean (RNWMM) operator, capable of handling multiple attributes with correlations, is introduced and its correlation qualities are investigated. Furthermore, a model for determining attribute weight is proposed specifically for the entropy-based method within the R-numbers environment. The two-stage decision-making approach is implemented using the inverse-order method. This method first prioritizes the alternatives in the later stage using regret theory. Then, it calculates the ideal alternative in the previous stage based on the three-way decision (3WD). The case study of risk assessment of base station network failures effectively demonstrates the adaptability and usefulness of the R-TSMAGDM approach.

关键词： Regret theory Three-way decision R-numbers multi-attribute group decision-making Two-stage decision-making

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A dynamic hybrid trust network-based dual-path feedback consensus model for multi-attribute group decision-making in intuitionistic fuzzy environment

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INFORMATION FUSION 2022年 80卷 266-281页

作者： Liu, Bingsheng Jiao, Shengxue Shen, Yinghua Chen, Yuan Wu, Guobin Chen, Si Tianjin Univ Coll Management & Econ Tianjin 300072 Peoples R China Chongqing Univ Sch Publ Policy & Adm Chongqing 400044 Peoples R China Chongqing Univ Sch Econ & Business Adm Chongqing 400044 Peoples R China Univ Adelaide Sch Architecture & Built Environm Adelaide SA 5000 Australia

This paper proposes a dual-path feedback consensus model based on dynamic hybrid trust relationships to solve multi-attribute group decision-making problems in intuitionistic fuzzy environment. This model comprises two main parts: (a) the construction of a dynamic hybrid trust network among decision makers (DMs) and (b) the formation of a dual-path feedback mechanism to improve the group consensus. In the first part, a hybrid trust network is constructed by combining DMs' prior knowledge of each other and the preference similarities between them. Then, the hybrid trust network is dynamically updated iteratively to reflect the changes in the trust relationships in the process of joint decision-making. In the second part, DMs with low consensus degrees are identified and provided with either a preference or weight adjustment path to improve the group consensus. The preference adjustment path is activated for DMs who agree to modify their preferences, and a nonlinear programming model is proposed to help DMs improve consensus degrees while minimizing adjustment cost. The weight adjustment path is activated for DMs who stick to their own opinions and refuse to make changes, and their weights is adjusted accordingly. An illustrative example along with the related sensitivity analysis and comparative study are used to verify the effectiveness of the proposed model.

关键词： multi-attribute group decision-making Intuitionistic fuzzy sets Trust network Feedback mechanism Dynamic decision-making

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The classification-based consensus in multi-attribute group decision-making

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2020年第9期71卷 1375-1389页

作者： Chen, Xin Xu, Weijun Liang, Haiming Dong, Yucheng South China Univ Technol Sch Business Adm Guangzhou Guangdong Peoples R China Sichuan Univ Sch Business Chengdu 610065 Sichuan Peoples R China

In multi-attribute group decision-making problem (MAGDM), the existing consensus reaching process (CRP) is to obtain a consensus ranking of alternatives. However, these CRPs contradict some real-life MAGDM problems in which decision-makers do not need to rank alternatives and hope to classify the alternatives into several groups instead. Thus, in this paper we propose a new CRP in MAGDM, called the classification-based consensus reaching process (CCRP). First, we present a feedback method with minimum adjustments to generate the optimal adjusted individual matrices via a 0-1 mixed linear programming model for CCRP. Subsequently, we develop the interactive consensus reaching process based on the feedback method with minimum adjustments in CCRP. Finally, a practical example from China Undergraduate Mathematical Contest in Modeling and a simulation analysis are conducted to demonstrate the validity of the proposed CCRP.

关键词： multi-attribute group decision-making consensus feedback method minimum adjustments classification

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A New Distance-Based Consensus Reaching Model for multi-attribute group decision-making with Linguistic Distribution Assessments

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INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS 2019年第1期12卷 395-409页

作者： Yao, Shengbao Zhongnan Univ Econ & Law Sch Business Adm Wuhan 430073 Hubei Peoples R China

This paper proposes a novel consensus reaching model for multi-attribute group decision making ( MAGDM) with information represented by means of linguistic distribution assessments. Firstly, some drawbacks of the existing distance measures for linguistic distribution assessments are analyzed by using numerical counterexamples, and a new distance measure is proposed for linguistic distribution assessments in order to alleviate the limitations. Then, a novel consensus reaching model is developed for MAGDM with linguistic distribution assessment, in which a feedback mechanism is devised by combining an identification rule and an optimization-based model. In this consensus framework, the model allows experts who are identified to modify their preferences to provide additional preference information about linguistic distribution assessments in each iteration. Meanwhile, by solving an optimization model, the consensus reaching model can automatically generate preference adjustment suggestions for experts. Moreover, the optimization model solved in each iteration minimizes the deviation between the adjusted values and initial preferences, which in turn leads to the good performance of the proposed consensus reaching model in preserving the initial preference information. Finally, an illustrative example shows that the proposed consensus reaching model is feasible and effective, and a comparative analysis highlights the advantages and characteristics of the model. (c) 2019 The Authors. Published by Atlantis Press SARL.

关键词： multi-attribute group decision-making Linguistic distribution assessments Consensus reaching Distance measure Optimization

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A novel three-way group investment decision model under intuitionistic fuzzy multi-attribute group decision-making environment

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INFORMATION SCIENCES 2021年 569卷 557-581页

作者： Jiang, Haibo Hu, Bao Qing Wuhan Univ Sch Math & Stat Wuhan 430072 Peoples R China Wuhan Univ Hubei Key Lab Computat Sci Wuhan 430072 Peoples R China

Three-way decision (3WD) provides a new research perspective for dealing with uncertain and complex investment decision-making problems. This paper aims to study a novel three-way group investment decision (3WGID) model under intuitionistic fuzzy multi attribute group decision-making (MAGDM) environment, which can deepen the understanding of 3WD and expand its applications in profit-based investment decision making problems. Firstly, we design the calculation methods of the relative cost and revenue functions of alternatives with the aid of attribute values expressed by intuitionistic fuzzy values. Subsequently, aiming at multiple attributes in MAGDM problems, we calculate the aggregated cost and revenue functions of alternatives in each evaluation matrix. Then, we integrate the aggregated cost functions and the aggregated revenue functions to obtain the relative profit functions of alternatives in each evaluation matrix. In the context of group decision-making, we determine the overall profit functions of alternatives by fusing the collective opinions of multiple experts. In addition, considering that there is no decision attribute in MAGDM problems, we use intuitionistic fuzzy TOPSIS method to estimate the conditional probability in each evaluation matrix and calculate the comprehensive conditional probability by an aggregation approach. With these discussions, a 3WGID model is established by Bayesian decision procedure and the maximum-profit principle. Meanwhile, the decision rules and associated profits of alternatives are further induced. Ultimately, a coalfield investment case study, along with a sensitivity analysis and a comparative analysis, is adopted to demonstrate the effectiveness and feasibility of the established 3WGID model. (c) 2021 Elsevier Inc. All rights reserved.

关键词： Three-way decision Intuitionistic fuzzy set multi-attribute group decision-making Maximum-profit principle Investment decision

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Probabilistic Dual-Hesitant Pythagorean Fuzzy Sets and Their Application in multi-attribute group decision-making

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COGNITIVE COMPUTATION 2021年第4期13卷 919-935页

作者： Ji, Chunliang Zhang, Runtong Wang, Jun Beijing Jiaotong Univ Sch Econ & Management Beijing 100044 Peoples R China Beijing Univ Chem Technol Sch Econ & Management Beijing 100029 Peoples R China

As modern socioeconomic decision-making problems are becoming more and more complex, it also becomes more and more difficult to appropriately depict decision makers' cognitive information in decision-making process. In addition, in group decision-making problems, decision makers' cognition is usually diverse, which makes it more complicated to express the overall preference information. Recently, the dual-hesitant Pythagorean fuzzy sets (DHPFSs) have been proved to be an effective tool to depict decision makers' evaluation values in multi-attribute group decision-making (MAGDM) procedure. The basic elements of DHPFSs are dual-hesitant Pythagorean fuzzy numbers (DHFNs), which are characterized by some possible membership degrees and non-membership degrees. In a DHFN, all members have the same importance, which indicates that multiple occurrence and appearance of some elements is ignored. Hence, the DHPFSs still have some drawbacks when expressing decision makers' evaluation information in MAGDM problems. This paper aims at proposing a novel tool to describe decision maker's evaluation values and apply it in solving MAGDM problems. This paper extends the traditional DHPFSs to probabilistic dual-hesitant Pythagorean fuzzy sets (PDHPFSs), which consider not only multiple membership and non-membership degrees, but also their probabilistic information. Afterward, we investigate the applications of PDHPFSs in MAGDM process. To this end, we first introduce the concept of DHPFSs as well as some related notions, such as operational rules, score function, accuracy function, comparison method, and distance measure. Second, based on the power average and Hamy mean, some aggregation operators for DHPFSs are presented. Properties of these new operators are also discussed. Third, we put forward a novel MAGDM method under PDHPFSs. A novel MAGDM method is developed, and further, we conduct numerical examples to show the performance and advantages of the new method. Results indicate t

关键词： Dual-hesitant Pythagorean fuzzy sets Probabilistic dual-hesitant Pythagorean fuzzy sets Power average Hamy mean multi-attribute group decision-making

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multi-attribute group decision-making based on Pythagorean fuzzy rough Aczel-Alsina aggregation operators and its applications to Medical diagnosis

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HELIYON 2023年第12期9卷 e23067页

作者： Hussain, Amir Zhu, Xiaoya Ullah, Kifayat Sarfaraz, Mehvish Yin, Shi Pamucar, Dragan Riphah Int Univ Lahore Dept Math Lahore 54000 Pakistan Soochow Univ Sch Polit & Publ Adm Suzhou Peoples R China Hebei Agr Univ Coll Econ & Management Baoding Peoples R China Univ Belgrade Fac Org Sci Dept Operat Res & Stat Belgrade Serbia Yuan Ze Univ Coll Engn Taoyuan Taiwan Lebanese Amer Univ Dept Comp Sci & Math Beirut Lebanon

The fusion of information is a very hectic process whenever we analyze the information. Several frameworks have been introduced to reduce the uncertainty while fusing the information. Among those techniques, the Pythagorean fuzzy rough set (PyFRS), which is based on approximations is a key idea for dealing with uncertainty when data is taken from real-world circumstances. Furthermore, the most adaptable and flexible operational laws based on the parameters for fuzzy frameworks are Aczel-Alsina t-norm (AATNM) and Aczel-Alsina t-conorm (AATCNM). The major goal of this work is to introduce some methods for the basic operations of the information in the shape of Pythagorean fuzzy rough (PyFR) values (PyFRVs). Consequently, the PyFR Aczel-Alsina weighted geometric (PyFRAAWG), PyFR Aczel-Alsina ordered weighted geometric (PyFRAAOWG), and PyFR Aczel-Alsina hybrid weighted geometric (PyFRAAHWG) operators are developed in this article based on AATNM and AATCNM. Further, some basic properties of the developed operators are observed and discussed. Further, the developed approaches are applied to the problem of multi-attribute group decision-making (MAGDM). The obtained results from the MAGDM problem are observed at various values of the parameters involved by AATNM and AATCNM. Moreover, the results are also compared with already existing techniques for the significance of the developed approach.

关键词： Pythagorean fuzzy rough set Aczel-alsina t-norm Aczel-alsina t-conorm multi-attribute group decision-making

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A novel approach to multi-attribute group decision-making based on q-rung orthopair fuzzy power dual Muirhead mean operators and novel score function

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2020年第1期39卷 561-580页

作者： Wang, Jun Tang, Fangcheng Shang, Xiaopu Xu, Yuan Bai, Kaiyuan Yan, Yusheng Beijing Univ Chem Technol Sch Econ & Management Beijing 100029 Peoples R China Beijing Jiaotong Univ Sch Econ & Management Beijing Peoples R China Beijing Jiaotong Univ Sch Mech Elect & Control Engn Beijing Peoples R China China Inst Marine Technol & Econ Beijing Peoples R China

The recently proposed q-rung orthopair fuzzy sets (q-ROFSs) have been proved to be an effective tool to describe decision makers' evaluation information and this paper attempts to propose a new multi-attribute group decision-making (MAGDM) method with q-rung orthopair fuzzy information. First of all, we propose a new score function of q-rung orthopair fuzzy numbers (q-ROFNs) by taking the hesitancy degree into account. When considering to fuse q-ROFNs, this paper tries to propose some novel aggregation operators. The power geometric (PG) operator has the ability of reducing or eliminating the bad influence of decision makers' unreasonable assessments on final decision results. Hence, we extend PG to q-ROFSs and propose the q-ROF power geometric operator and its weighted form. The most prominent advantage of dual Muirhead mean (DMM) is that it can capture the interrelationships among any numbers of input arguments. To take full advantages of PG and DMM, we further combine PG with DMM within q-rung orthopair fuzzy environment and propose the q-rung orthopair fuzzy power dual Muirhead mean, and q-rung orthopair fuzzy weighted power dual Muirhead mean operators. The proposed operators can reduce the negative effects of unreasonable evaluations on the decision results, and simultaneously take the interrelationship among any numbers of input arguments into account. In addition, we propose a new MAGDM method based on the proposed aggregation operators. Finally, we provide numerical examples to demonstrate the validity and merits of the proposed method.

关键词： q-rung orthopair fuzzy set power geometric operator dual muirhead mean q-rung orthopair fuzzy power dual muirhead mean novel score function multi-attribute group decision-making

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