A ranking method with a preference relation based on the PROMETHEE method in incomplete multi-scale information systems

[1]  Jianming Zhan,et al.  An investigation on Wu-Leung multi-scale information systems and multi-expert group decision-making , 2021, Expert Syst. Appl..

[2]  Jianming Zhan,et al.  A three-way decision methodology to multi-attribute decision-making in multi-scale decision information systems , 2021, Inf. Sci..

[3]  Qinghua Zhang,et al.  Optimal scale selection and attribute reduction in multi-scale decision tables based on three-way decision , 2020, Inf. Sci..

[4]  Mohammad Mahdi Mousavi,et al.  The application of PROMETHEE multi-criteria decision aid in financial decision making: Case of distress prediction models evaluation , 2020, Expert Syst. Appl..

[5]  Zeshui Xu,et al.  Multi-attribute dynamic two-sided matching method of talent sharing market in incomplete preference ordinal environment , 2020, Appl. Soft Comput..

[6]  Enrique Herrera-Viedma,et al.  A new multi-criteria decision model based on incomplete dual probabilistic linguistic preference relations , 2020, Appl. Soft Comput..

[7]  Yee Leung,et al.  A comparison study of optimal scale combination selection in generalized multi-scale decision tables , 2020, Int. J. Mach. Learn. Cybern..

[8]  Peide Liu,et al.  Normal wiggly hesitant fuzzy linguistic power Hamy mean aggregation operators and their application to multi-attribute decision-making , 2020, Comput. Ind. Eng..

[9]  Jiye Liang,et al.  Multi-granularity three-way decisions with adjustable hesitant fuzzy linguistic multigranulation decision-theoretic rough sets over two universes , 2020, Inf. Sci..

[10]  Pengsen Liu,et al.  Uncertain multi-attribute group decision making based on linguistic-valued intuitionistic fuzzy preference relations , 2020, Inf. Sci..

[11]  Wei-Zhi Wu,et al.  Inclusion measure-based multi-granulation decision-theoretic rough sets in multi-scale intuitionistic fuzzy information tables , 2020, Inf. Sci..

[12]  Weizhong Dai,et al.  Generalized multi-scale decision tables with multi-scale decision attributes , 2019, Int. J. Approx. Reason..

[13]  Yiyu Yao,et al.  TOPSIS method based on a fuzzy covering approximation space: An application to biological nano-materials selection , 2019, Inf. Sci..

[14]  Jianming Zhan,et al.  Covering-Based Variable Precision $(\mathcal {I},\mathcal {T})$-Fuzzy Rough Sets With Applications to Multiattribute Decision-Making , 2019, IEEE Transactions on Fuzzy Systems.

[15]  Kai Wang,et al.  A group decision making sustainable supplier selection approach using extended TOPSIS under interval-valued Pythagorean fuzzy environment , 2019, Expert Syst. Appl..

[16]  Yong Shi,et al.  Public blockchain evaluation using entropy and TOPSIS , 2019, Expert Syst. Appl..

[17]  Kai Zhang,et al.  Fuzzy β-covering based (I, T)-fuzzy rough set models and applications to multi-attribute decision-making , 2019, Comput. Ind. Eng..

[18]  Hamido Fujita,et al.  Updating three-way decisions in incomplete multi-scale information systems , 2019, Inf. Sci..

[19]  Jianming Zhan,et al.  Covering based multigranulation (I, T)-fuzzy rough set models and applications in multi-attribute group decision-making , 2019, Inf. Sci..

[20]  Bingzhen Sun,et al.  Variable precision multigranulation rough fuzzy set approach to multiple attribute group decision-making based on λ-similarity relation , 2019, Comput. Ind. Eng..

[21]  Zhong Zheng,et al.  Rule acquisition and optimal scale selection in multi-scale formal decision contexts and their applications to smart city , 2017, Future Gener. Comput. Syst..

[22]  Chen Hao,et al.  Optimal scale selection in dynamic multi-scale decision tables based on sequential three-way decisions , 2017, Inf. Sci..

[23]  K. S. Ravichandran,et al.  A new extension to PROMETHEE under intuitionistic fuzzy environment for solving supplier selection problem with linguistic preferences , 2017, Appl. Soft Comput..

[24]  Zeshui Xu,et al.  The new extension of TOPSIS method for multiple criteria decision making with hesitant Pythagorean fuzzy sets , 2017, Appl. Soft Comput..

[25]  Jun Wang,et al.  Stepwise optimal scale selection for multi-scale decision tables via attribute significance , 2017, Knowl. Based Syst..

[26]  Concepción Maroto,et al.  A multiple criteria supplier segmentation using outranking and value function methods , 2017, Expert Syst. Appl..

[27]  Feng Li,et al.  A new approach of optimal scale selection to multi-scale decision tables , 2017, Inf. Sci..

[28]  Wei-Zhi Wu,et al.  On rule acquisition in incomplete multi-scale decision tables , 2017, Inf. Sci..

[29]  Hongying Zhang,et al.  Approaches to group decision making with incomplete information based on power geometric operators and triangular fuzzy AHP , 2015, Expert Syst. Appl..

[30]  Chao Wang,et al.  Multi-criteria group decision making with incomplete hesitant fuzzy preference relations , 2015, Appl. Soft Comput..

[31]  Jiuping Xu,et al.  A new outranking choice method for group decision making under Atanassov's interval-valued intuitionistic fuzzy environment , 2014, Knowl. Based Syst..

[32]  Zeshui Xu,et al.  Multi-criteria decision making with intuitionistic fuzzy PROMETHEE , 2014, J. Intell. Fuzzy Syst..

[33]  V. Lakshmana Gomathi Nayagam,et al.  A complete ranking of incomplete interval information , 2014, Expert Syst. Appl..

[34]  Yee Leung,et al.  Optimal scale selection for multi-scale decision tables , 2013, Int. J. Approx. Reason..

[35]  Wei-Zhi Wu,et al.  On knowledge acquisition in multi-scale decision systems , 2013, Int. J. Mach. Learn. Cybern..

[36]  Yee Leung,et al.  Theory and applications of granular labelled partitions in multi-scale decision tables , 2011, Inf. Sci..

[37]  Wei-xiang Li,et al.  An extension of the Promethee II method based on generalized fuzzy numbers , 2009, 2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009).

[38]  George Mavrotas,et al.  Application in a Students’ Selection Problem , 2009, J. Decis. Syst..

[39]  Zeshui Xu,et al.  Intuitionistic preference relations and their application in group decision making , 2007, Inf. Sci..

[40]  Yee Leung,et al.  Knowledge acquisition in incomplete information systems: A rough set approach , 2006, Eur. J. Oper. Res..

[41]  Johan Springael,et al.  PROMETHEE and AHP: The design of operational synergies in multicriteria analysis.: Strengthening PROMETHEE with ideas of AHP , 2004, Eur. J. Oper. Res..

[42]  Yee Leung,et al.  Maximal consistent block technique for rule acquisition in incomplete information systems , 2003, Inf. Sci..

[43]  Salvatore Greco,et al.  Handling Missing Values in Rough Set Analysis of Multi-Attribute and Multi-Criteria Decision Problems , 1999, RSFDGrC.

[44]  Marzena Kryszkiewicz,et al.  Rough Set Approach to Incomplete Information Systems , 1998, Inf. Sci..

[45]  Zdzis?aw Pawlak,et al.  Rough sets , 2005, International Journal of Computer & Information Sciences.

[46]  Ronald R. Yager,et al.  On ordered weighted averaging aggregation operators in multicriteria decisionmaking , 1988, IEEE Trans. Syst. Man Cybern..

[47]  Jean Pierre Brans,et al.  HOW TO SELECT AND HOW TO RANK PROJECTS: THE PROMETHEE METHOD , 1986 .