RAIRO-Oper. Res.
Volume 56, Number 3, May-June 2022
Decision and Optimization in Service, Control and Engineering (CoDIT2019-DOSCE)
Page(s) 1491 - 1501
Published online 13 June 2022
  • D. Aikhuele and S. Odofin, Generalized triangular intuitionistic fuzzy geometric averaging operator for decision making in engineering. Information 8 (2017) 78. [CrossRef] [Google Scholar]
  • C. Araz and I. Ozkarahan, Supplier evaluation and management system for strategic sourcing based on a new multicriteria sorting procedure. Int. J. Prod. Econ. 106 (2007) 585–606. [CrossRef] [Google Scholar]
  • D.V. Assche and Y. De Smet, FlowSort parameters elicitation based on categorization examples. Int. J. Multicriteria Decis. Making 6 (2016) 191–210. [CrossRef] [Google Scholar]
  • K.T. Atanassov, Intuitionistic fuzzy sets. Fuzzy Sets Syst. 20 (1986) 87–96. [Google Scholar]
  • C.A. Bana, E. Costa, J.M. Corte and J.C. Vansnick, Multiple Criteria Decision Analysis: State of the Art Surveys. Springer, New York (2005). [Google Scholar]
  • S. Banerjee, Arithmetic operations on generalized trapezoidal fuzzy number and its applications. Turk. J. Fuzzy Syst. 3 (2012) 16–44. [Google Scholar]
  • A.C. Campos, B. Mareschal and A. Almeida, Fuzzy FlowSort: an integration of the FlowSort method and Fuzzy Set Theory for decision making on the basis of inaccurate quantitative data. Inf. Sci. 293 (2015) 115–123. [CrossRef] [Google Scholar]
  • T.Y. Chen, The inclusion-based TOPSIS method with interval-valued intuitionistic fuzzy sets for multiple criteria group decision making. Appl. Soft Comput. 26 (2015) 57–73. [CrossRef] [Google Scholar]
  • B.E. Costa and A. Carlos, Les problématiques de l’aide à la d’décision: vers l’enrichissement de la trilogie choix-tri-rangement. RAIRO-Oper. Res. 30 (1996) 191–216. [CrossRef] [EDP Sciences] [Google Scholar]
  • D. Dubois and H. Prade, The legacy of 50 years of fuzzy sets: a discussion. Fuzzy Sets Syst. 281 (2015) 21–31. [CrossRef] [Google Scholar]
  • E. Fernandez and J. Avarro, A new approach to multi-criteria sorting based on fuzzy outranking relations: the THESEUS method. Eur. J. Oper. Res. 213 (2011) 405–413. [Google Scholar]
  • J. Figueira, Y. de Smet and J.P. Brans, MCDA methods for sorting and clustering problems: Promethee TRI and Promethee CLUSTER. Université Libre de Bruxelles, Service deMathématiques de la Gestion Working Paper (2004). [Google Scholar]
  • A. Gani and S. Abbas, A new average method for solving intuitionistic fuzzy transportation problem. Int. J. Pure Appl. Math. 93 (2014) 491–499. [CrossRef] [Google Scholar]
  • S.S. Gautam and S.R. Singh, TOPSIS for multi criteria decision making in intuitionistic fuzzy environment. Int. J. Comput. App. 156 (2016) 42–49. [Google Scholar]
  • C.L. Hwang and K. Yoon, Multiple Attributes Decision Making Methods and Applications. Springer, Berlin Heidelberg (1981). [CrossRef] [Google Scholar]
  • A. Ishizaka and M. Gordon, MACBETHSort: a multiple criteria decision method for sorting strategic products. J. Oper. Res. Soc. 68 (2017) 53–61. [CrossRef] [Google Scholar]
  • A. Ishizaka and V. Pereira, Utilisation of ANPSort for sorting alternative with interdependent criteria illustrated through a researcher’s classification problem in an academic context. Soft Comput. 24 (2020) 13639–13650. [CrossRef] [Google Scholar]
  • A. Ishizaka, C. Pearman and P. Nemery, AHPSort: an AHP-based method for sorting problems. Int. J. Prod. Res. 50 (2012) 4767–4784. [CrossRef] [Google Scholar]
  • P. Janssen and P. Nemery, An extension of the FlowSort sorting method to deal with imprecision, 4OR-Q J. Oper. Res. 11 (2012) 171–193. [Google Scholar]
  • D.F. Li, J.X. Nan and M.J. Zhang, A ranking method of triangular intuitionistic fuzzy numbers and application to decision making. Int. J. Comput. Intell. Syst. 3 (2012) 522–530. [Google Scholar]
  • F. Lolli, A. Ishizaka, R. Gamberini, B. Rimini and M. Messori, FlowSort-GDSS – a novel group multi-criteria decision support system for sorting problems with application to fmea. Expert Syst. App. 42 (2015) 6342–6349. [CrossRef] [Google Scholar]
  • G.S. Mahapatra and T.K. Roy, Reliability evaluation using triangular intuitionistic fuzzy numbers arithmetic operations. World Acad. Sci. Eng. Technol. 50 (2009) 574–581. [Google Scholar]
  • I. Mahdavi, N. Mahdavi-Amiri, A. Heidarzade and R. Nourifar, Designing a model of fuzzy TOPSIS in multiple criteria decision making. Appl. Math. Comput. 206 (2008) 607–617. [MathSciNet] [Google Scholar]
  • P. Nemery and C. Lamboray, FlowSort: a flow-based sorting method with limiting or central profiles. TOP (Off. J. Span. Soc. Stat. Oper. Res.) 16 (2008) 90–113. [Google Scholar]
  • J.H. Park, H.J. Cho and Y.C. Kwun, Extension of the VIKOR method for group decision making with interval-valued intuitionistic fuzzy information. Fuzzy Optim. Decis. Making 10 (2011) 233–253. [Google Scholar]
  • R. Pelissari, M.C. Oliveira, S.B. Amor and A.J. Abackerli, A new FlowSort-based method to deal with information imperfections in sorting decision-making problems. Eur. J. Oper. Res. 276 (2019) 235–246. [CrossRef] [Google Scholar]
  • A. Sengupta and T.K. Pal, On comparing interval numbers: a study on existing ideas. Stud. Fuzziness Soft Comput. 238 (2009) 25–37. [CrossRef] [Google Scholar]
  • S. Singh, Intuitionistic fuzzy DEA/AR and its application to flexible manufacturing systems. RAIRO: Oper. Res. 52 (2018) 241–257. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
  • W. Yu, ELECTRE TRI. Aspects méthodologiques et guide d’utilisation, Document du LAMSADE, Université Paris-Dauphine (1992). [Google Scholar]
  • L.A. Zadeh, Fuzzy sets. Inf. Control 8 (1965) 338–353. [Google Scholar]
  • X. Zhang, F. Jin and P. Liu, A grey relational projection method for multi-attribute decision making based on intuitionistic trapezoidal fuzzy number. Appl. Math. Modell. 37 (2013) 3467–3477. [CrossRef] [Google Scholar]

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