Neutrosophic N-Soft Sets with TOPSIS method for Multiple Attribute Decision Making

The objective of this article is to introduce a new hybrid model of neutrosophic N-soft set which is combination of neutrosophic set and N-soft set. We introduce some basic operations on neutrosophic N-soft sets along with their fundamental properties. For multi-attribute decisionmaking (MADM) problems with neutrosophic N-soft sets, we propose an extended TOPSIS (technique based on order preference by similarity to ideal solution) method. In this method, we first propose a weighted decision matrix based comparison method to identify the positive and the negative ideal solutions. Afterwards, we define a separation measurement of these solutions. Finally, we calculate relative closeness to identify the optimal alternative. At length, a numerical example is rendered to illustrate the developed scheme in medical diagnosis via hypothetical case study.

[1]  Ching-Lai Hwang,et al.  Methods for Multiple Attribute Decision Making , 1981 .

[2]  Muhammad Riaz,et al.  Bipolar fuzzy soft mappings with application to bipolar disorders , 2019, International Journal of Biomathematics.

[3]  F. Smarandache A Unifying Field in Logics: Neutrosophic Logic. , 1999 .

[4]  Muhammad Akram,et al.  TOPSIS Approach for MAGDM Based on Interval-Valued Hesitant Fuzzy N-Soft Environment , 2018, International Journal of Fuzzy Systems.

[5]  FengFeng,et al.  Soft sets combined with fuzzy sets and rough sets , 2010, SOCO 2010.

[6]  Harish Garg,et al.  Novel scaled prioritized intuitionistic fuzzy soft interaction averaging aggregation operators and their application to multi criteria decision making , 2018, Eng. Appl. Artif. Intell..

[7]  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.

[8]  Masooma Raza Hashmi,et al.  MAGDM for agribusiness in the environment of various cubic m-polar fuzzy averaging aggregation operators , 2019, J. Intell. Fuzzy Syst..

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

[10]  Xindong Peng,et al.  Pythagorean fuzzy soft MCGDM methods based on TOPSIS, VIKOR and aggregation operators , 2019, J. Intell. Fuzzy Syst..

[11]  Masooma Raza Hashmi,et al.  A novel approach to censuses process by using Pythagorean m-polar fuzzy Dombi's aggregation operators , 2020, J. Intell. Fuzzy Syst..

[12]  Zeshui Xu,et al.  Extension of TOPSIS to Multiple Criteria Decision Making with Pythagorean Fuzzy Sets , 2014, Int. J. Intell. Syst..

[13]  Syeda Tayyba Tehrim,et al.  Cubic bipolar fuzzy ordered weighted geometric aggregation operators and their application using internal and external cubic bipolar fuzzy data , 2019, Comput. Appl. Math..

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

[15]  Aslam Muhammad,et al.  N-soft topology and its applications to multi-criteria group decision making , 2019, J. Intell. Fuzzy Syst..

[16]  Zeshui Xu,et al.  Hesitant fuzzy multi-attribute decision making based on TOPSIS with incomplete weight information , 2013, Knowl. Based Syst..

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

[18]  M. Gorzałczany A method for inference in approximate reasoning based on interval-valued fuzzy sets , 1987 .

[19]  Ting-Yu Chen,et al.  The interval-valued fuzzy TOPSIS method and experimental analysis , 2008, Fuzzy Sets Syst..

[20]  Muhammad Akram,et al.  New decision-making hybrid model: intuitionistic fuzzy N-soft rough sets , 2019, Soft Computing.

[21]  Masooma Raza Hashmi,et al.  Linear Diophantine fuzzy set and its applications towards multi-attribute decision-making problems , 2019, J. Intell. Fuzzy Syst..

[22]  Muhammad Akram,et al.  Group decision-making methods based on hesitant N-soft sets , 2019, Expert Syst. Appl..

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

[24]  Florentin Smarandache,et al.  m-Polar Neutrosophic Topology with Applications to Multi-criteria Decision-Making in Medical Diagnosis and Clustering Analysis , 2019, International Journal of Fuzzy Systems.

[25]  Urapati,et al.  TOPSIS for Solving Multi-Attribute Decision Making Problems under Bi-Polar Neutrosophic Environment , 2016 .

[26]  Masooma Raza Hashmi,et al.  Soft rough Pythagorean m-polar fuzzy sets and Pythagorean m-polar fuzzy soft rough sets with application to decision-making , 2019, Computational and Applied Mathematics.

[27]  Ahmed Aboelfetouh,et al.  An Integrated Neutrosophic-TOPSIS Approach and Its Application to Personnel Selection: A New Trend in Brain Processing and Analysis , 2019, IEEE Access.

[28]  Muhammad Riaz,et al.  Multi-attribute group decision making based on cubic bipolar fuzzy information using averaging aggregation operators , 2019, J. Intell. Fuzzy Syst..

[29]  Xindong Peng,et al.  Approaches to single-valued neutrosophic MADM based on MABAC, TOPSIS and new similarity measure with score function , 2018, Neural Computing and Applications.

[30]  Muhammad Riaz,et al.  Novel concepts of soft rough set topology with applications , 2019, J. Intell. Fuzzy Syst..

[31]  Muhammad Riaz,et al.  Pythagorean m-polar fuzzy sets and TOPSIS method for the selection of advertisement mode , 2019, J. Intell. Fuzzy Syst..

[32]  Muhammad Akram,et al.  A Novel Trapezoidal Bipolar Fuzzy TOPSIS Method for Group Decision-Making , 2018, Group Decision and Negotiation.

[33]  Harish Garg,et al.  Dual Hesitant Fuzzy Soft Aggregation Operators and Their Application in Decision-Making , 2018, Cognitive Computation.

[34]  Muhammad Riaz,et al.  A novel extension of TOPSIS to MCGDM with bipolar neutrosophic soft topology , 2019, J. Intell. Fuzzy Syst..

[35]  Mohamed Abdel-Basset,et al.  Neutrosophic Multi-Criteria Decision Making Approach for IoT-Based Enterprises , 2019, IEEE Access.

[36]  Muhammad Shabir,et al.  On soft topological spaces , 2011, Comput. Math. Appl..

[37]  Muhammad Akram,et al.  Fuzzy N-soft sets: A novel model with applications , 2018, J. Intell. Fuzzy Syst..

[38]  Florentin Smarandache,et al.  On Soft Rough Topology with Multi-Attribute Group Decision Making , 2019, Mathematics.

[39]  Florentin Smarandache,et al.  Neutrosophic Set is a Generalization of Intuitionistic Fuzzy Set, Inconsistent Intuitionistic Fuzzy Set (Picture Fuzzy Set, Ternary Fuzzy Set), Pythagorean Fuzzy Set, q-Rung Orthopair Fuzzy Set, Spherical Fuzzy Set, etc , 2019, 1911.07333.

[40]  Chen-Tung Chen,et al.  Extensions of the TOPSIS for group decision-making under fuzzy environment , 2000, Fuzzy Sets Syst..

[41]  Young Bae Jun,et al.  An adjustable approach to fuzzy soft set based decision making , 2010, J. Comput. Appl. Math..

[42]  J. Martina Jency,et al.  Fuzzy Neutrosophic Soft Topological Spaces , 2013 .

[43]  Harish Garg,et al.  Generalized intuitionistic fuzzy soft power aggregation operator based on t‐norm and their application in multicriteria decision‐making , 2018, Int. J. Intell. Syst..

[44]  Jiang-Xia Nan,et al.  Extension of the TOPSIS for Multi-Attribute Group Decision Making under Atanassov IFS Environments , 2011, Int. J. Fuzzy Syst. Appl..

[45]  Sanjay Kumar,et al.  Intuitionistic fuzzy entropy and distance measure based TOPSIS method for multi-criteria decision making , 2014 .

[46]  José Carlos Rodriguez Alcantud,et al.  N-soft sets and their decision making algorithms , 2017, Soft Computing.

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

[48]  Naim Çagman,et al.  Soft topology , 2015, Comput. Math. Appl..

[49]  Victor I. Chang,et al.  Towards a Reuse Strategic Decision Pattern Framework – from Theories to Practices , 2018, Information Systems Frontiers.

[50]  Rajshekhar Sunderraman,et al.  Single Valued Neutrosophic Sets , 2010 .

[51]  Bijan Davvaz,et al.  An application of intuitionistic fuzzy sets in medicine , 2016 .