Enhancing PROMETHEE method with intuitionistic fuzzy soft sets

The notion of intuitionistic fuzzy soft sets (IFSSs) provides an effective tool for solving multiple attribute decision making with intuitionistic fuzzy information. The most crucial issue in decision making based on IFSSs is how to derive the ranking of alternatives from the information quantified in terms of intuitionistic fuzzy values. In this study, we propose a new extension of the preference ranking organization method for enrichment evaluation (PROMETHEE), by taking advantage of IFSSs. In addition to presenting a myriad of new notions, such as intuitionistic fuzzy membership (or nonmembership) deviation matrices, intuitionistic fuzzy membership (or nonmembership) preference matrices, and aggregated intuitionistic fuzzy preference matrices, we put more emphasis on the construction of three distinct preference structures and related utility functions on the corresponding weakly ordered sets by considering the positive, negative, and net flows of the alternatives based on the aggregated intuitionistic fuzzy preference matrix. We present a new algorithm for solving multiple attribute decision‐making problems with the extended PROMETHEE method based on IFSSs. Moreover, a benchmark problem concerning risk investment is investigated to give a comparative analysis and show the feasibility of our approach.

[1]  Muhammad Irfan Ali,et al.  Algebraic structures of soft sets associated with new operations , 2011, Comput. Math. Appl..

[2]  Z. S. Xu,et al.  Models for Multiple Attribute Decision Making with Intuitionistic Fuzzy Information , 2007, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[3]  Saifur Rahman,et al.  On cuts of Atanassov's intuitionistic fuzzy sets with respect to fuzzy connectives , 2016, Inf. Sci..

[4]  Harish Garg,et al.  Bonferroni mean aggregation operators under intuitionistic fuzzy soft set environment and their applications to decision-making , 2018, J. Oper. Res. Soc..

[5]  Harish Garg,et al.  Generalized and group-based generalized intuitionistic fuzzy soft sets with applications in decision-making , 2017, Applied Intelligence.

[6]  Ronald R. Yager,et al.  Pythagorean Membership Grades in Multicriteria Decision Making , 2014, IEEE Transactions on Fuzzy Systems.

[7]  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..

[8]  Young Bae Jun,et al.  Applications of soft sets in ideal theory of BCK/BCI-algebras , 2008, Inf. Sci..

[9]  Harish Garg,et al.  A nonlinear-programming methodology for multi-attribute decision-making problem with interval-valued intuitionistic fuzzy soft sets information , 2017, Applied Intelligence.

[10]  ChenYihua,et al.  The maximizing deviation method for group multiple attribute decision making under linguistic environment , 2007 .

[11]  Liang-Hsuan Chen,et al.  Dual Bipolar Measures of Atanassov's Intuitionistic Fuzzy Sets , 2014, IEEE Transactions on Fuzzy Systems.

[12]  Ronald R. Yager,et al.  Another View on Generalized Intuitionistic Fuzzy Soft Sets and Related Multiattribute Decision Making Methods , 2019, IEEE Transactions on Fuzzy Systems.

[13]  Alev Taskin Gumus,et al.  A fuzzy logic based PROMETHEE method for material selection problems , 2018 .

[14]  Dragan Pamučar,et al.  A Novel Approach for the Selection of Power-Generation Technology Using a Linguistic Neutrosophic CODAS Method: A Case Study in Libya , 2018, Energies.

[15]  Ronald R. Yager,et al.  Multicriteria Decision Making With Ordinal/Linguistic Intuitionistic Fuzzy Sets For Mobile Apps , 2016, IEEE Transactions on Fuzzy Systems.

[16]  Zeshui Xu,et al.  An outranking sorting method for multi-criteria group decision making using intuitionistic fuzzy sets , 2016, Inf. Sci..

[17]  Francisco Herrera,et al.  Linguistic decision analysis: steps for solving decision problems under linguistic information , 2000, Fuzzy Sets Syst..

[18]  Zeshui Xu,et al.  Information fusion for intuitionistic fuzzy decision making: An overview , 2016, Information Fusion.

[19]  Shyi-Ming Chen,et al.  Handling multicriteria fuzzy decision-making problems based on vague set theory , 1994 .

[20]  Feng Liu,et al.  A multicriteria model for the selection of the transport service provider: A single valued neutrosophic DEMATEL multicriteria model , 2018, Decision Making: Applications in Management and Engineering.

[21]  Harish Garg,et al.  A robust aggregation operators for multi-criteria decision-making with intuitionistic fuzzy soft set environment , 2017 .

[22]  Bijan Davvaz,et al.  Soft sets combined with fuzzy sets and rough sets: a tentative approach , 2010, Soft Comput..

[23]  Alessio Ishizaka,et al.  Multi-criteria Decision Analysis: Methods and Software , 2013 .

[24]  Witold Pedrycz,et al.  Soft set based association rule mining , 2016, Knowl. Based Syst..

[25]  José Carlos R. Alcantud,et al.  Centroid Transformations of Intuitionistic Fuzzy Values Based on Aggregation Operators , 2018, Mathematics.

[26]  Gui-Wu Wei,et al.  Maximizing deviation method for multiple attribute decision making in intuitionistic fuzzy setting , 2008, Knowl. Based Syst..

[27]  Fuyuan Xiao,et al.  A Hybrid Fuzzy Soft Sets Decision Making Method in Medical Diagnosis , 2018, IEEE Access.

[28]  P. Vincke,et al.  Note-A Preference Ranking Organisation Method: The PROMETHEE Method for Multiple Criteria Decision-Making , 1985 .

[29]  Xiaoyan Liu,et al.  On some new operations in soft set theory , 2009, Comput. Math. Appl..

[30]  Rita Gamberini,et al.  On the elicitation of criteria weights in PROMETHEE-based ranking methods for a mobile application , 2019, Expert Syst. Appl..

[31]  Humberto Bustince,et al.  On averaging operators for Atanassov's intuitionistic fuzzy sets , 2011, Inf. Sci..

[32]  Krassimir T. Atanassov,et al.  Intuitionistic fuzzy sets , 1986 .

[33]  D. Molodtsov Soft set theory—First results , 1999 .

[34]  Ronald R. Yager,et al.  Generalized Orthopair Fuzzy Sets , 2017, IEEE Transactions on Fuzzy Systems.

[35]  Zeshui Xu,et al.  Some geometric aggregation operators based on intuitionistic fuzzy sets , 2006, Int. J. Gen. Syst..

[36]  José Carlos Rodriguez Alcantud,et al.  Some formal relationships among soft sets, fuzzy sets, and their extensions , 2016, Int. J. Approx. Reason..

[37]  A. R. Roy,et al.  Soft set theory , 2003 .

[38]  Muhammad Akram,et al.  A NEW MULTIPLE CRITERIA DECISION-MAKING METHOD BASED ON BIPOLAR FUZZY SOFT GRAPHS , 2018 .

[39]  Ronald R. Yager,et al.  Lexicographic Orders of Intuitionistic Fuzzy Values and Their Relationships , 2019, Mathematics.

[40]  Feng Feng,et al.  Soft subsets and soft product operations , 2013, Inf. Sci..

[41]  Muhammad Irfan Ali,et al.  Logic Connectives for Soft Sets and Fuzzy Soft Sets , 2014, IEEE Transactions on Fuzzy Systems.

[42]  Dug Hun Hong,et al.  Multicriteria fuzzy decision-making problems based on vague set theory , 2000, Fuzzy Sets Syst..

[43]  Zeshui Xu,et al.  Intuitionistic Fuzzy Aggregation Operators , 2007, IEEE Transactions on Fuzzy Systems.

[44]  Luis Martínez-López,et al.  Improving decision making approaches based on fuzzy soft sets and rough soft sets , 2018, Appl. Soft Comput..

[45]  Harish Garg,et al.  A robust correlation coefficient measure of dual hesitant fuzzy soft sets and their application in decision making , 2018, Eng. Appl. Artif. Intell..

[46]  Harish Garg,et al.  Algorithms for interval-valued fuzzy soft sets in emergency decision making based on WDBA and CODAS with new information measure , 2018, Computers & Industrial Engineering.

[47]  Zeshui Xu,et al.  Uncertain Multi-Attribute Decision Making , 2015 .

[48]  José Carlos R. Alcantud,et al.  An $N$-Soft Set Approach to Rough Sets , 2020, IEEE Transactions on Fuzzy Systems.

[49]  Robert LIN,et al.  NOTE ON FUZZY SETS , 2014 .

[50]  Harish Garg,et al.  Maclaurin symmetric mean aggregation operators based on t-norm operations for the dual hesitant fuzzy soft set , 2019, Journal of Ambient Intelligence and Humanized Computing.

[51]  Darko Bozanic,et al.  Multi-criteria FUCOM – Fuzzy MABAC model for the selection of location for construction of single-span bailey bridge , 2019, Decision Making: Applications in Management and Engineering.

[52]  Pinaki Majumdar,et al.  Generalised fuzzy soft sets , 2010, Comput. Math. Appl..

[53]  Athar Kharal,et al.  On Fuzzy Soft Sets , 2009, Adv. Fuzzy Syst..

[54]  Zeshui Xu,et al.  Intuitionistic and interval-valued intutionistic fuzzy preference relations and their measures of similarity for the evaluation of agreement within a group , 2009, Fuzzy Optim. Decis. Mak..

[55]  Muhammad Irfan Ali,et al.  A note on soft sets, rough soft sets and fuzzy soft sets , 2011, Appl. Soft Comput..

[56]  Young Bae Jun,et al.  Soft sets and soft rough sets , 2011, Inf. Sci..

[57]  Dragan Pamučar,et al.  NORMALIZED WEIGHTED GEOMETRIC BONFERRONI MEAN OPERATOR OF INTERVAL ROUGH NUMBERS – APPLICATION IN INTERVAL ROUGH DEMATEL-COPRAS , 2018, Facta Universitatis, Series: Mechanical Engineering.

[58]  Ronald R. Yager,et al.  Golden Rule and Other Representative Values for Atanassov Type Intuitionistic Membership Grades , 2015, IEEE Transactions on Fuzzy Systems.

[59]  Zhibin Wu,et al.  The maximizing deviation method for group multiple attribute decision making under linguistic environment , 2007, Fuzzy Sets Syst..