Three-way group decisions under hesitant fuzzy linguistic environment for green supplier selection

The purpose of this paper is to propose a three-way group decision-making approach to address the selection of green supplier, by extending decision-theoretic rough set (DTRS) into hesitant fuzzy linguistic (HFL) environment, considering the flexible evaluation expression format of HFL term set (HFLTS) and the idea of minimum expected risk in DTRS.,Specifically, the authors first present the calculation method of the conditional probability and discuss the loss functions of DTRS with HFL element (HFLE), along with some associated properties being investigated in detail. Further, three-way group decisions rules can be deduced, followed by the cost of every green supplier candidate. Thus, based on these discussions, a novel green supplier selection DTRS model that combines multi-criteria group decision-making (MCGDM) and HFLTS is designed.,A numerical example of green supplier selection, the comparative analysis and associated discussions are conducted to illustrate the applicability and novelty of the presented model.,The selection of green supplier has played a critically strategic role in sustainable enterprise development due to continuous environmental concerns. This paper offers an insight for companies to select green supplier selection from the perspective of three-way group decisions.,This paper uses three-way decisions to address green supplier selection in the HFL context, which is considered as a MCGDM issue.

[1]  Ali H. Diabat,et al.  Integrated fuzzy multi criteria decision making method and multi-objective programming approach for supplier selection and order allocation in a green supply chain , 2013 .

[2]  Jianping Fan,et al.  Green supplier selection with undesirable outputs DEA under Pythagorean fuzzy environment , 2019, J. Intell. Fuzzy Syst..

[3]  Felix T. S. Chan,et al.  A fuzzy AHP and fuzzy multi-objective linear programming model for order allocation in a sustainable supply chain: A case study , 2017, Int. J. Comput. Integr. Manuf..

[4]  Joseph Sarkis,et al.  Green supplier development: analytical evaluation using rough set theory , 2010 .

[5]  Ahmad Makui,et al.  Interval-Valued Hesitant Fuzzy Method based on Group Decision Analysis for Estimating Weights of Decision Makers , 2016 .

[6]  Ming Tang,et al.  Managing information measures for hesitant fuzzy linguistic term sets and their applications in designing clustering algorithms , 2019, Inf. Fusion.

[7]  Huai-Wei Lo,et al.  An integrated model for solving problems in green supplier selection and order allocation , 2018, Journal of Cleaner Production.

[8]  Mohsen Akbarpour Shirazi,et al.  An extended intuitionistic fuzzy modified group complex proportional assessment approach , 2018 .

[9]  R. Sivakumar,et al.  Green supplier selection and order allocation in a low-carbon paper industry: integrated multi-criteria heterogeneous decision-making and multi-objective linear programming approaches , 2015, Annals of Operations Research.

[10]  Bao Qing Hu,et al.  Three-way decisions space and three-way decisions , 2014, Inf. Sci..

[11]  Decui Liang,et al.  A Novel Risk Decision Making Based on Decision-Theoretic Rough Sets Under Hesitant Fuzzy Information , 2015, IEEE Transactions on Fuzzy Systems.

[12]  Peide Liu,et al.  A novel three-way decision model under multiple-criteria environment , 2019, Inf. Sci..

[13]  Zeshui Xu Deviation measures of linguistic preference relations in group decision making , 2005 .

[14]  H. Gitinavard,et al.  Evaluating the sustainable mining contractor selection problems: An imprecise last aggregation preference selection index method , 2017, Journal of Sustainable Mining.

[15]  Francisco Herrera,et al.  Double hierarchy hesitant fuzzy linguistic term set and MULTIMOORA method: A case of study to evaluate the implementation status of haze controlling measures , 2017, Inf. Fusion.

[16]  Zeshui Xu,et al.  Three-way decisions based on decision-theoretic rough sets with dual hesitant fuzzy information , 2017, Inf. Sci..

[17]  Jing Li,et al.  Sustainable supplier selection based on SSCM practices: A rough cloud TOPSIS approach , 2019, Journal of Cleaner Production.

[18]  Zhang-peng Tian,et al.  Green Supplier Selection Using Improved TOPSIS and Best-Worst Method Under Intuitionistic Fuzzy Environment , 2018, Informatica.

[19]  Zeshui Xu,et al.  Heterogeneous multi-attribute nonadditivity fusion for behavioral three-way decisions in interval type-2 fuzzy environment , 2019, Inf. Sci..

[20]  Yahia ZareMehrjerdi,et al.  Developing Fuzzy TOPSIS Method based on Interval-valued Fuzzy Sets , 2012 .

[21]  Jyoti Pareek,et al.  Automatic Identification of Learning Object Type , 2012 .

[22]  Xiaonan Li,et al.  Heterogeneous multigranulation fuzzy rough set-based multiple attribute group decision making with heterogeneous preference information , 2018, Comput. Ind. Eng..

[23]  Jiye Liang,et al.  Hesitant fuzzy linguistic rough set over two universes model and its applications , 2018, Int. J. Mach. Learn. Cybern..

[24]  Zeshui Xu,et al.  Approaches to manage hesitant fuzzy linguistic information based on the cosine distance and similarity measures for HFLTSs and their application in qualitative decision making , 2015, Expert Syst. Appl..

[25]  Mir Saman Pishvaee,et al.  A hierarchical multi-criteria group decision-making method based on TOPSIS and hesitant fuzzy information , 2017, Int. J. Appl. Decis. Sci..

[26]  Zengtai Gong,et al.  Covering multigranulation trapezoidal fuzzy decision-theoretic rough fuzzy set models and applications , 2016, J. Intell. Fuzzy Syst..

[27]  Zeshui Xu,et al.  Hesitant fuzzy information aggregation in decision making , 2011, Int. J. Approx. Reason..

[28]  Francisco Herrera,et al.  Hesitant Fuzzy Linguistic Term Sets for Decision Making , 2012, IEEE Transactions on Fuzzy Systems.

[29]  Shu-Ping Wan,et al.  Supplier selection using ANP and ELECTRE II in interval 2-tuple linguistic environment , 2017, Inf. Sci..

[30]  R. Mostaghel,et al.  Circular business model challenges and lessons learned - An industrial perspective , 2018 .

[31]  Dong Myung Lee,et al.  A portfolio model for component purchasing strategy and the case study of two South Korean elevator manufacturers , 2010 .

[32]  Yiyu Yao,et al.  Three-way decisions with probabilistic rough sets , 2010, Inf. Sci..

[33]  Zeshui Xu,et al.  Distance and similarity measures for hesitant fuzzy linguistic term sets and their application in multi-criteria decision making , 2014, Inf. Sci..

[34]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning-III , 1975, Inf. Sci..

[35]  Xiaonan Li,et al.  Three-way decisions approach to multiple attribute group decision making with linguistic information-based decision-theoretic rough fuzzy set , 2018, Int. J. Approx. Reason..

[36]  Joseph Sarkis,et al.  Multicriteria Green Supplier Segmentation , 2017, IEEE Transactions on Engineering Management.

[37]  Yiyu Yao,et al.  A Decision Theoretic Framework for Approximating Concepts , 1992, Int. J. Man Mach. Stud..

[38]  Shulin Tang,et al.  Green supplier selection model with hesitant fuzzy information , 2017, J. Intell. Fuzzy Syst..

[39]  Xia Xiao,et al.  Three-way group decision making based on multigranulation fuzzy decision-theoretic rough set over two universes , 2017, Int. J. Approx. Reason..

[40]  Jing Li,et al.  Sustainability evaluation via variable precision rough set approach: A photovoltaic module supplier case study , 2018, Journal of Cleaner Production.

[41]  Zeshui Xu,et al.  Qualitative decision making with correlation coefficients of hesitant fuzzy linguistic term sets , 2015, Knowl. Based Syst..

[42]  Joseph Sarkis,et al.  Complex investment decisions using rough set and fuzzy c-means: An example of investment in green supply chains , 2016, Eur. J. Oper. Res..

[43]  Jinwoo Park,et al.  An integrative framework for supplier relationship management , 2010, Ind. Manag. Data Syst..

[44]  Zeshui Xu,et al.  A New Aggregation Method-Based Error Analysis for Decision-Theoretic Rough Sets and Its Application in Hesitant Fuzzy Information Systems , 2017, IEEE Transactions on Fuzzy Systems.

[45]  Andrea Baronchelli,et al.  Machine Learning the Cryptocurrency Market , 2018, Complex..

[46]  Mir Saman Pishvaee,et al.  Green supplier evaluation in manufacturing systems: a novel interval-valued hesitant fuzzy group outranking approach , 2018, Soft Comput..