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Application of multiattribute decision-making methods for the determination of relative significance factor of impact categories

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ENVIRONMENTAL MANAGEMENT 2003年第5期31卷 633-641页

作者： Noh, J Lee, KM Ajou Univ Sch Environm & Urban Engn Suwon 442749 South Korea

A relative significance factor (f(i)) of an impact category is the external weight of the impact category. The objective of this study is to propose a systematic and easy-to-use method for the determination of f(i). multiattribute decision-making (MADM) methods including the analytical hierarchy process (AHP), the rank-order centroid method, and the fuzzy method were evaluated for this purpose. The results and practical aspects of using the three methods are compared. Each method shows the same trend, with minor differences in the value of f(i). Thus, all three methods can be applied to the determination of f(i). The rank order centroid method reduces the number of pairwise comparisons by placing the alternatives in order, although it has inherent weakness over the fuzzy method in expressing the degree of vagueness associated with assigning weights to criteria and alternatives. The rank order centroid method is considered a practical method for the determination of f(i) because it is easier and simpler to use compared to the AHP and the fuzzy method.

关键词： multiattribute decision-making analytical hierarchy process fuzzy method rank-order centroid method weighting relative significance factor

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Hierarchical Sequential Three-Way multiattribute decision-making Method Based on Regret Theory in Multiscale Fuzzy decision Systems

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IEEE TRANSACTIONS ON FUZZY SYSTEMS 2024年第9期32卷 4961-4975页

作者： Qian, Jin Lu, Yuehua Yu, Ying Zhou, Jie Miao, Duoqian East China Jiaotong Univ Sch Software Nanchang 330013 Jiangxi Peoples R China Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen 518060 Peoples R China Tongji Univ Comp Sci & Technol Shanghai 201804 Peoples R China

Most of the existing multiattribute decision-making models under multiscale decision information systems are established by selecting the optimal scale or fusing multiscale information into a single scale. These models will lose part of the decision information, resulting in inaccurate decision results. However, sequential three-way decision can not only process information hierarchically, but also provide delayed decision between acceptance and rejection. In addition, the irrational behavior of decision-makers will have a certain impact on the decision-making results. To this end, for multiscale and diversity decision-making problems, this article proposes a hierarchical sequential three-way multiattribute decision-making method based on regret theory. Specifically, to represent this diversity, the multiscale evaluation information table is converted into a digital evaluation value table through a fuzzy membership function. Second, based on the regret-rejoicing function of regret theory, the regret-rejoicing relation of alternatives in multiscale information systems is established, which can be used to calculate the conditional probability. Third, the relative loss functions based on regret theory are proposed by considering the psychological behaviors of decision-makers. Finally, the hierarchical sequential three-way multiattribute decision-making method for solving the multiscale decision-making problem is proposed. The stability and effectiveness of the proposed method are verified by the corresponding experiments and the comparative analysis of practical cases. The proposed method solves the fusion problem of multiscale decision information and obtains flexible ranking results according to the risk factor.

关键词： Hierarchical sequential three-way decision multiattribute decision-making multiscale fuzzy decision systems regret theory regret-rejoicing function Hierarchical sequential three-way decision multiattribute decision-making multiscale fuzzy decision systems regret theory regret-rejoicing function

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Development and evaluation of five fuzzy multiattribute decision-making methods

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INTERNATIONAL JOURNAL OF APPROXIMATE REASONING 1996年第4期14卷 281-310页

作者： Triantaphyllou, E Lin, CT Department of Industrial Engineering Louisiana State University Baton Rouge Louisiana USA

We present the development of five fuzzy multiattribute decision-making methods. These methods are based on the analytic hierarchy process (original and ideal mode), the weighted-sum model, the weighted-product model, and the TOPSIS method. Moreover, these methods are examined in terms of two evaluative criteria. Computational results on test problems suggest that although all the methods are inaccurate, some of them seem to be more accurate than the others. The proposed evaluation methodology can easily be used in evaluating more fuzzy multiattribute decision making methods.

关键词： fuzzy decision-making multiattribute decision-making ranking of fuzzy numbers pairwise comparisons analytic hierarchy process weighted-sum model weighted-product model TOPSIS method

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Three-Way multiattribute decision-making Based on Outranking Relations

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IEEE TRANSACTIONS ON FUZZY SYSTEMS 2021年第10期29卷 2844-2858页

作者： Zhan, Jianming Jiang, Haibo Yao, Yiyu Hubei Minzu Univ Dept Math Enshi 445000 Enshi 445000 Peoples R China Univ Regina Dept Comp Sci Regina SK S4S 0A2 Canada

In contrast to two-way decisions (2WD), three-way decisions (3WD) can effectively reduce decision risks by utilizing a new delayed decision option. This article incorporates 3WD into multiattribute decision-making (MADM) based on an outranking relation. We construct the outranked set for each alternative and introduce a hybrid information table that combines an MADM matrix with a loss function table. We propose three strategies to design a new 3WD model for MADM. The rationality and effectiveness of the proposed 3WD method are demonstrated by solving a problem of enterprise project investment target selections. Finally, we provide the comparative analysis and two experimental evaluations. The results show that the proposed 3WD method is effective and practically useful.

关键词： decision making Rough sets Indexes Investment Adaptation models Uncertainty decision-theoretic rough fuzzy set (DTRFS) multiattribute decision-making outranking relation three-way decision

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Modeling Interactive multiattribute decision-making via Probabilistic Linguistic Term Set Extended by Dempster-Shafer Theory

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INTERNATIONAL JOURNAL OF FUZZY SYSTEMS 2021年第2期23卷 599-613页

作者： Fei, Liguo Feng, Yuqiang Harbin Inst Technol Sch Management Harbin 150001 Peoples R China

In multiattribute decision-making (MADM), more and more attention is paid to the interaction between attributes when considering the actual decision environment. As a result, interactive MADM has become an emerging and challenging area of research whose success will greatly facilitate the development of decision-making. This paper models the interactive MADM problem and its contribution is multifaceted. First, the concept of probabilistic linguistic term set (PLTS) is extended by Dempster-Shafer theory (DST), which helps to express more uncertain information, followed by some basic operations, such as score function and aggregation operator. In virtue of evidential best-worst method and the principle of maximum entropy, then a novel nonadditive measure determination method is developed based on the 2-order additive measure to better model the interaction between attributes. Further, the generalized PLTS-based Choquet integral is defined by which generalized PLTSs on a nonadditive measure can be reasonably aggregated. Finally, an interactive MADM model is constructed and the technical details are described. The proposed approach is implemented to select the supplier for medical devices, and its effectiveness is emphasized by comparison with other methods.

关键词： Dempster– Shafer theory Probabilistic linguistic term set multiattribute decision-making Interaction Nonadditive measure

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Fuzzy mathematical programming approach to heterogeneous multiattribute decision-making with interval-valued intuitionistic fuzzy truth degrees

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INFORMATION SCIENCES 2015年 325卷 484-503页

作者： Wan, Shu-Ping Li, Deng-Feng Fuzhou Univ Sch Econ & Management Fuzhou 350108 Fujian Peoples R China Jiangxi Univ Finance & Econ Coll Informat Technol Nanchang 330013 Peoples R China

Considering the hesitancy degrees on pair-wise comparisons of alternatives as interval-valued intuitionistic fuzzy (IVIF) sets (IVIFSs), we develop a new fuzzy mathematical programming method for solving heterogeneous multiattribute decision-making problems based on the Linear Programming Technique for Multidimensional Analysis of Preference. In this method, IVIFSs, intuitionistic fuzzy sets (IFSs), trapezoidal fuzzy numbers, linguistic variables, intervals and real numbers are used to represent multiple types of attribute values and the attribute weights are not completely known. The preference relations between alternatives given by decision maker are expressed with IVIFSs of ordered pairs of alternatives. The consistency and inconsistency indices are defined as IVIFSs on the basis of comparisons of alternatives with IVIF truth degrees. The attribute weights and fuzzy ideal solution (FIS) are estimated through constructing a fuzzy mathematical programming model, which is solved by the technically developed method of IVIF mathematical programming. Hereby the distances of alternatives to the FIS are computed to rank the alternatives. Some generalization and discussion on the constructed IVIF mathematical programming model are also presented. A green supplier selection example is provided to illustrate the effectiveness of the proposed model and method. The comparison analyses verify the superiorities of the proposed method. (C) 2015 Elsevier Inc. All rights reserved.

关键词： multiattribute decision-making Fuzzy mathematical programming Interval-valued intuitionistic fuzzy set Linear Programming Technique for Multidimensional Analysis of Preference Green supply chain

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Rise of multiattribute decision-making in combating COVID-19: A systematic review of the state-of-the-art literature

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INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS 2022年第6期37卷 3514-3624页

作者： Alsalem, Mohammed Assim Mohammed, Rawia Albahri, Osamah Shihab Zaidan, Aws Alaa Alamoodi, Abdullah Hussein Dawood, Kareem Alnoor, Alhamzah Albahri, Ahmed Shihab Zaidan, Bilal Bahaa Alsattar, Hassan Alazab, Mamoun Jumaah, Fawaz Univ Pendidikan Sultan Idris Fac Arts Comp & Creat Ind Dept Comp Tanjung Malim 35900 Malaysia Geomatika Univ Coll Fac Comp & Innovat Technol Kuala Lumpur Malaysia Komar Univ Sci & Technol KUST Comp Sci Dept Sulaymaniyah Iraq Univ Sains Malaysia Sch Management George Town Malaysia Iraqi Commiss Computers & Informat ICCI Informat Inst Postgrad Studies IIPS Baghdad Iraq Natl Yunlin Univ Sci & Technol Future Technol Res Ctr Touliu Taiwan Charles Darwin Univ Coll Engn IT & Environm Casuarina NT Australia Intel Corp Dept Adv Applicat & Embedded Syst George Town Malaysia

Considering the coronavirus disease 2019 (COVID-19) pandemic, the government and health sectors are incapable of making fast and reliable decisions, particularly given the various effects of decisions on different contexts or countries across multiple sectors. Therefore, leaders often seek decision support approaches to assist them in such scenarios. The most common decision support approach used in this regard is multiattribute decision-making (MADM). MADM can assist in enforcing the most ideal decision in the best way possible when fed with the appropriate evaluation criteria and aspects. MADM also has been of great aid to practitioners during the COVID-19 pandemic. Moreover, MADM shows resilience in mitigating consequences in health sectors and other fields. Therefore, this study aims to analyse the rise of MADM techniques in combating COVID-19 by presenting a systematic literature review of the state-of-the-art COVID-19 applications. Articles on related topics were searched in four major databases, namely, Web of Science, IEEE Xplore, ScienceDirect, and Scopus, from the beginning of the pandemic in 2019 to April 2021. Articles were selected on the basis of the inclusion and exclusion criteria for the identified systematic review protocol, and a total of 51 articles were obtained after screening and filtering. All these articles were formed into a coherent taxonomy to describe the corresponding current standpoints in the literature. This taxonomy was drawn on the basis of four major categories, namely, medical (n = 30), social (n = 4), economic (n = 13) and technological (n = 4). Deep analysis for each category was performed in terms of several aspects, including issues and challenges encountered, contributions, data set, evaluation criteria, MADM techniques, evaluation and validation and bibliography analysis. This study emphasised the current standpoint and opportunities for MADM in the midst of the COVID-19 pandemic and promoted additional efforts towards unde

关键词： COVID-19 decision support multiattribute decision-making multicriteria decision-making SARS-CoV-2

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Improved possibility degree method for ranking intuitionistic fuzzy numbers and their application in multiattribute decision-making

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GRANULAR COMPUTING 2019年第2期4卷 237-247页

作者： Garg, Harish Kumar, Kamal Thapar Inst Engn & Technol Sch Math Patiala 147004 Punjab India

In the present paper, we define an improved possibility degree method to rank the different intuitionistic fuzzy numbers (IFNs). To achieve it, we first present some shortcomings of the existing possibility degree method and score function of IFNs. The existing shortcomings are overcome by proposing a new possibility degree measure for IFNs. The desirable properties of it are analyzed in details. Afterward, based on proposed possibility degree measure, a decision-making approach presents to solve the multiattribute decision-making (MADM) problem under the intuitionistic fuzzy set environment. Finally, a real-life case is studied to manifest the practicability and feasibility of the proposed decision-making method.

关键词： multiattribute decision-making Possibility degree measure Intuitionistic fuzzy set Informative measures

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Optimization of Group multiattribute decision-making Model in Commercial Space Investment

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Journal of Shanghai Jiaotong university(Science) 2023年第6期28卷 831-840页

作者：张一鸣侯俊杰钟少文 China Aerospace Academy of Systems Science and Engineering Beijing 100048China China Great Wall Industry Corporation Beijing 100054China

A group multiattribute decision-making model was proposed by implementing prospect theory,multi-attribute decision-making,group decision-making and entropy methods for the optimization in commercial space ***,the decision-making function was decided using prospect theory by the preference of each expert to reach the comprehensive prospect value based on different investment options;second,expert decision weights were reached according to entropy method;third,the expert group decision-making information was congregated according to the group decision-making congregation algorithm to reach the most optimized investment option;finally,an example was given to demonstrate the feasibility and effectiveness of the *** model com-prehensively takes the advantages of many methods to congregate experts'experiences and avoid the subjective influences,thus providing a scientific decision-making approach for the commercial space investment.

关键词： commercial space investment multiattribute decision-making group decision-making prospect theory entropy theory

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Cubic q-Rung Orthopair Fuzzy Linguistic Set and Their Application to multiattribute decision-making with Muirhead Mean Operator

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Journal of Artificial Intelligence and Technology 2021年第1期1卷 37-50页

作者： Harish Garg Tahir Mahmood Jabbar Ahmmad Qaisar Khan Zeeshan Ali School of Mathematics Thapar Institute of Engineering and TechnologyDeemed UniversityPatiala 147004PunjabIndia Department of Mathematics and Statistics International Islamic UniversityIslamabadPakistan Department of Mathematics Northern UniversityNowsheraPakistan

The objective of this paper is to present a new concept,named cubic q-rung orthopair fuzzy linguistic set(Cq-ROFLS),to quantify the uncertainty in the *** proposed Cq-ROFLS is a qualitative form of cubic q-rung orthopair fuzzy set,where membership degrees and nonmembership degrees are represented in terms of linguistic *** basic notions of Cq-ROFLS have been introduced and study their basic operations and ***,to aggregate the different pairs of preferences,we introduce the Cq-ROFL Muirhead mean-(MM),weighted MM-,dual MM-based *** major advantage of considering the MM is that it considers the interrelationship between more than two arguments at a *** the other hand,the Cq-ROFLS has the ability to describe the qualitative information in terms of linguistic *** properties and relation of the derived operators are *** addition,we also investigate multiattribute decision-making problems under the Cq-ROFLS environment and illustrate with a numerical ***,the effectiveness and advantages of the work are established by comparing with other methods.

关键词： cubic q-rung orthopair fuzzy linguistic set Muirhead mean operators multiattribute decision-making

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