Fuzzy set theoretic approach of assigning weights to objectives in multieriteria decision making

1989 ◽  
Vol 20 (8) ◽  
pp. 1381-1386 ◽  
Author(s):  
J. R. RAO ◽  
NILIMA ROY
MATEMATIKA ◽  
2018 ◽  
Vol 34 (1) ◽  
pp. 49-58 ◽  
Author(s):  
Shiva Raj Singh ◽  
Surendra Singh Gautam ◽  
Abhishekh .

In general most of real life problem of decision making involve imprecise parameters. In recent past the major emphasis of research workers in this area have been to develop the reliable models to deal with such imprecision and vagueness effectively. Several theories have been developed such as fuzzy set theory, interval valued fuzzy set, intuitionistic fuzzy set, and interval valued intuitionistic fuzzy set, rough set and soft set. The primary objectives of all the above developed theories are to deal with various kinds of uncertainty, imprecision and vagueness but unfortunately every theory has certain limitations. In the present paper we briefly introduced the notion of soft set, fuzzy soft set and intuitionistic fuzzy soft set. We extend the Jurio et al construction method of converting fuzzy set into intuitionistic fuzzy set to fuzzy soft set into intuitionistic fuzzy soft set. Here we consider a problem of decision making in fuzzy soft set and presented a method to generalize it into intuitionistic fuzzy soft set based decision making problem for modelling the problem in a better way. In the process we used the construction method and score function of intuitionistic fuzzy number.


1990 ◽  
Vol 29 (04) ◽  
pp. 386-392 ◽  
Author(s):  
R. Degani ◽  
G. Bortolan

AbstractThe main lines ofthe program designed for the interpretation of ECGs, developed in Padova by LADSEB-CNR with the cooperation of the Medical School of the University of Padova are described. In particular, the strategies used for (i) morphology recognition, (ii) measurement evaluation, and (iii) linguistic decision making are illustrated. The main aspect which discerns this program in comparison with other approaches to computerized electrocardiography is its ability of managing the imprecision in both the measurements and the medical knowledge through the use of fuzzy-set methodologies. So-called possibility distributions are used to represent ill-defined parameters as well as threshold limits for diagnostic criteria. In this way, smooth conclusions are derived when the evidence does not support a crisp decision. The influence of the CSE project on the evolution of the Padova program is illustrated.


2021 ◽  
pp. 1-13
Author(s):  
Paul Augustine Ejegwa ◽  
Shiping Wen ◽  
Yuming Feng ◽  
Wei Zhang ◽  
Jia Chen

Pythagorean fuzzy set is a reliable technique for soft computing because of its ability to curb indeterminate data when compare to intuitionistic fuzzy set. Among the several measuring tools in Pythagorean fuzzy environment, correlation coefficient is very vital since it has the capacity to measure interdependency and interrelationship between any two arbitrary Pythagorean fuzzy sets (PFSs). In Pythagorean fuzzy correlation coefficient, some techniques of calculating correlation coefficient of PFSs (CCPFSs) via statistical perspective have been proposed, however, with some limitations namely; (i) failure to incorporate all parameters of PFSs which lead to information loss, (ii) imprecise results, and (iii) less performance indexes. Sequel, this paper introduces some new statistical techniques of computing CCPFSs by using Pythagorean fuzzy variance and covariance which resolve the limitations with better performance indexes. The new techniques incorporate the three parameters of PFSs and defined within the range [-1, 1] to show the power of correlation between the PFSs and to indicate whether the PFSs under consideration are negatively or positively related. The validity of the new statistical techniques of computing CCPFSs is tested by considering some numerical examples, wherein the new techniques show superior performance indexes in contrast to the similar existing ones. To demonstrate the applicability of the new statistical techniques of computing CCPFSs, some multi-criteria decision-making problems (MCDM) involving medical diagnosis and pattern recognition problems are determined via the new techniques.


Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 440
Author(s):  
Aldo Joel Villa Silva ◽  
Luis Pérez-Domínguez ◽  
Erwin Martínez Gómez ◽  
David Luviano-Cruz ◽  
Delia Valles-Rosales

Dimensional analysis under linguistic Pythagorean fuzzy set (DA-LPFS) is a technique to handle qualitative (intangible) as well as the interactions between criteria, by combining dimensional analysis (DA) and Pythagorean fuzzy set (PFS) with linguistic variables. In this paper, a novel DA method is proposed for LPFSs based in a PFS extension, in order to consider the mutual relationship among criteria and handle qualitative (fuzzy) and quantitative (crisp) information usually involved in Multi-criteria decision making (MCDM) problems. Finally, DA-LPFS is applied to handle a case concerning the selection of CNC router to illustrate the applicability of the method.


2021 ◽  
pp. 1-18
Author(s):  
Le Jiang ◽  
Hongbin Liu

The use of probabilistic linguistic term sets (PLTSs) means the process of computing with words. The existing methods computing with PLTSs mainly use symbolic model. To provide a semantic model for computing with PLTSs, we propose to represent a PLTS by using an interval type-2 fuzzy set (IT2FS). The key step is to compute the footprint of uncertainty of the IT2FS. To this aim, the upper membership function is computed by aggregating the membership functions of the linguistic terms contained in the PLTS, and the lower membership function is obtained by moving the upper membership function downward with the step being total entropy of the PLTS. The comparison rules, some operations, and an aggregation operator for PLTSs are introduced. Based on the proposed method of computing with PLTSs, a multi-criteria group decision making model is introduced. The proposed decision making model is then applied in green supplier selection problem to show its feasibility.


Axioms ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 145
Author(s):  
Yun Jin ◽  
Zareena Kousar ◽  
Kifayat Ullah ◽  
Tahir Mahmood ◽  
Nimet Yapici Pehlivan ◽  
...  

Interval-valued T-spherical fuzzy set (IVTSFS) handles uncertain and vague information by discussing their membership degree (MD), abstinence degree (AD), non-membership degree (NMD), and refusal degree (RD). MD, AD, NMD, and RD are defined in terms of closed subintervals of that reduce information loss compared to the T-spherical fuzzy set (TSFS), which takes crisp values from intervals; hence, some information may be lost. The purpose of this manuscript is to develop some Hamacher aggregation operators (HAOs) in the environment of IVTSFSs. To do so, some Hamacher operational laws based on Hamacher t-norms (HTNs) and Hamacher t-conorms (HTCNs) are introduced. Using Hamacher operational laws, we develop some aggregation operators (AOs), including an interval-valued T-spherical fuzzy Hamacher (IVTSFH) weighted averaging (IVTSFHWA) operator, an IVTSFH-ordered weighted averaging (IVTSFHOWA) operator, an IVTSFH hybrid averaging (IVTSFHHA) operator, an IVTSFH-weighted geometric (IVTSFHWG) operator, an IVTSFH-ordered weighted geometric (IVTSFHOWG) operator, and an IVTSFH hybrid geometric (IVTSFHHG) operator. The validation of the newly developed HAOs is investigated, and their basic properties are examined. In view of some restrictions, the generalization and proposed HAOs are shown, and a multi-attribute decision-making (MADM) procedure is explored based on the HAOs, which are further exemplified. Finally, a comparative analysis of the proposed work is also discussed with previous literature to show the superiority of our work.


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