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Granular Computing
Published in: Granular Computing 3/2021

22-04-2020 | Original Paper

Decision-making approach based on Pythagorean Dombi fuzzy soft graphs

Authors: Muhammad Akram, Gulfam Shahzadi

Published in: Granular Computing | Issue 3/2021

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Abstract

A Pythagorean fuzzy set model is more useful than intuitionistic fuzzy set model to handle the imprecise information involving both membership and nonmembership degrees, and a soft set is an other parameterized point of view for handling the vagueness. A Pythagorean fuzzy soft graph is considered more capable than intuitionistic fuzzy soft graph for representing the parametric relationships between objects, and the Dombi operators with operational parameters have creditable extensibility. Based on these two notions, we propose the concept of Pythagorean Dombi fuzzy soft graph (PDFSG). We describe certain concepts of graph theory under Pythagorean Dombi fuzzy soft environment. Further, we define the degree sequence and degree set in PDFSG, and the concept of edge regular PDFSG with consequential properties. Moreover, we illustrate the examples in decision making including selection of suitable ETL software for a business intelligence project and evaluation of electronics companies. Finally, we present the comparison analysis of our proposed model to show the superiority than existing model.
previous article Complex Pythagorean Dombi fuzzy graphs for decision making
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Literature
Akram M, Ali G (2020) Hybrid models for decision making based on rough Pythagorean fuzzy bipolar soft information. Granul Comput 5(1):1–15MathSciNetCrossRef
Akram M, Dudek WA, Dar JM (2019) Pythagorean Dombi fuzzy aggregation operators with application in multicriteria decision making. Int J Intell Syst 34(11):3000–3019CrossRef
Akram M, Dar JM, Naz S (2020) Pythagorean Dombi fuzzy graphs. Complex Intell Syst 6:29–54CrossRef
Akram M, Nawaz S (2016) Fuzzy soft graphs with applications. J Intell Fuzzy Syst 30(6):3619–3632CrossRef
Ali MI (2011) A note on soft sets, rough soft sets and fuzzy soft sets. Appl Soft Comput 11(4):3329–3332CrossRef
Ali MI, Feng F, Liu X, Min WK, Shabir M (2009) On some new operations in soft set theory. Comput Math Appl 57(9):1547–1553MathSciNetCrossRef
Ashraf S, Naz S, Kerre EE (2018) Dombi fuzzy graphs. Fuzzy Inf Eng 10(1):58–79CrossRef
Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20(1):87–96CrossRef
Bai SM, Chen SM (2008a) Automatically constructing grade membership functions of fuzzy rules for students evaluation. Expert Syst Appl 35(3):1408–1414
Bai SM, Chen SM (2008b) Automatically constructing concept maps based on fuzzy rules for adapting learning systems. Expert Syst Appl 35(1–2):41–49
Chen SM (1996) A fuzzy reasoning approach for rule-based systems based on fuzzy logics. IEEE Trans Syst Man Cybern B (Cybern) 26(5):769–778CrossRef
Chen SM, Cheng SH (2016) Fuzzy multi-attribute decision making based on transformation techniques of intuitionistic fuzzy values and intuitionistic fuzzy geometric averaging operators. Inf Sci 352:133–149CrossRef
Chen SM, Cheng SH, Lan TC (2016a) A novel similarity measure between intuitionistic fuzzy sets based on the centroid points of transformed fuzzy numbers with applications to pattern recognition. Inf Sci 343:15–40MathSciNetCrossRef
Chen SM, Cheng SH, Lan TC (2016b) Multi-criteria decision making based on the TOPSIS method and similarity measures between intuitionistic fuzzy values. Inf Sci 367:279–295CrossRef
Chen SM, Manalu GMT, Pan JS, Liu HC (2013) Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and particle swarm optimization techniques. IEEE Trans Cybern 43(3):1102–1117CrossRef
Chen J, Ye J (2017) Some single-valued neutrosophic Dombi weighted aggregation operators for multiple attribute decision making. Symmetry 9(6):82CrossRef
Dombi J (1982) A general class of fuzzy operators, the De Morgan class of fuzzy operators and fuzziness measures induced by fuzzy operators. Fuzzy Sets Syst 8(2):149–163MathSciNetCrossRef
Dubois D, Ostasiewicz W, Prade H (2000) Fuzzy sets: history and basic notions. Handbook of fuzzy sets and possibility theory. Springer, New York, pp 121–124CrossRef
Feng F, Li C, Davvaz B, Ali MI (2011a) Soft sets combined with fuzzy sets and rough sets: a tentative approach. Soft Comput 14(9):899–911CrossRef
Hamacher H (1978) On logical aggregations of non-binar explicit decision criteria. Rita G. Fischer Verlag, Frankfurt
Jana C, Pal M, Wang JQ (2019) Bipolar fuzzy Dombi aggregation operators and its application in multiple-attribute decision making process. J Ambient Intell Human Comput 10(9):3533–3549CrossRef
Klement EP, Mesiar R, Pap E (2013) Triangular norms, vol 8. Springer Science and Business Media, BerlinMATH
Kuwagaki A (1952) On the rational functional equation of function unknown of two variables. Mem Coll Sci 28(2)
Liu P, Liu J, Chen SM (2018) Some intuitionistic fuzzy Dombi Bonferroni mean operators and their application to multi-attribute group decision making. J Oper Res Soc 69(1):1–24MathSciNetCrossRef
Liu P, Chen SM, Liu J (2017) Multiple-attribute group decision making based on intuitionistic fuzzy interaction partitioned Bonferroni mean operators. Inf Sci 411:98–121MathSciNetCrossRef
Liu X, Wang L (2020) An extension approach of TOPSIS method with OWAD operator for multiple criteria decision making. Granul Comput 5(1):135–148CrossRef
Mishra AR, Chandel A, Motwani D (2020) Extended MABAC method based on divergence measures for multi-criteria assessment of programming language with interval-valued intuitionistic fuzzy sets. Granul Comput 5(1):97–117CrossRef
Naz S, Ashraf S, Akram M (2018) A novel approach to decision making with Pythagorean fuzzy information. Mathematics 6:1–28CrossRef
Parvathi R, Karunambigai MG (2006) Intuitionistic fuzzy graphs. Computational intelligence, theory and applications. Springer, Berlin, pp 139–150
Peng X, Yang Y, Song J, Jiang Y (2015) Pythagorean fuzzy soft set and its application. Comput Eng 41(7):224–229
Rosenfeld A (1975) Fuzzy graphs, fuzzy sets and their applications. Academic Press, New York, pp 77–95
Roy AR, Maji PK (2007) A fuzzy soft set theoretic approach to decision making problems. J Comput Appl Math 203(2):461–472MathSciNetCrossRef
Schweizer B, Sklar S (1983) Probabilistic metric spaces. Probab Appl Math
Som T (2006) On the theory of soft sets, soft relations and fuzzy soft relation. In: Proceedings of the national conference on uncertainty: a mathematical approach, UAMA-06, Burdwan, pp 1–9
Thumbakara RK, George B (2014) Soft graphs. Gen Math Notes 21(2):75–86
Yager RR (2013) Pythagorean fuzzy subsets. In: 2013 Joint IFSA world congress and NAFIPS annual meeting (IFSA/NAFIPS). IEEE, pp 57–61
Zhang X, Xu Z (2014) Extension of TOPSIS to multiple criteria decision making with Pythagorean fuzzy sets. Int J Intell Syst 29(12):1061–1078CrossRef
Metadata
Title
Decision-making approach based on Pythagorean Dombi fuzzy soft graphs
Authors
Muhammad Akram
Gulfam Shahzadi
Publication date
22-04-2020
Publisher
Springer International Publishing
Published in
Granular Computing / Issue 3/2021
Print ISSN: 2364-4966
Electronic ISSN: 2364-4974
DOI
https://doi.org/10.1007/s41066-020-00224-4

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