Dr. Rishu Arora - Academia.edu (original) (raw)
Papers by Dr. Rishu Arora
Lecture notes in networks and systems, 2023
International Journal of Lightweight Materials and Manufacture
International Journal of Lightweight Materials and Manufacture, 2022
Advances in Intelligent Systems and Computing, 2019
The manuscript aims to create a few aggregation operators based on Einstein norms under intuition... more The manuscript aims to create a few aggregation operators based on Einstein norms under intuitionistic fuzzy (IF) soft set environment. For this, some operational laws based on Einstein sum and product are discussed. Then, based on these operations, Einstein averaging and geometric operators such as IF soft weighted Einstein averaging (IFSWEA) and IF soft weighted Einstein geometric (IFSWEG) operator are proposed. Further, some of their properties are investigated and the relationship between the proposed operators and the existing ones is explored. Furthermore, an approach for solving DM problems has been presented and illustrated with an example for demonstrating the effectiveness of proposed work.
Artificial Intelligence Review, 2020
Intuitionistic fuzzy soft set (IFSS) accommodates more uncertainties within the information by co... more Intuitionistic fuzzy soft set (IFSS) accommodates more uncertainties within the information by considering the parameterization feature than the intuitionistic fuzzy sets and hence its applications are more extensive. Archimedean T-conorm and T-norm (ATT), consists of T-norm and T-conorm classes, is as an essential source to make the comprehensive operational laws. Meanwhile, the Maclaurin symmetric mean (MSM) has a prominent characteristic and the advantage that it can take into account the interrelation between multi-input arguments, including different attributes or different experts. Motivated by these chief characteristics, in this article, we extend the MSM operators to the IFSS based on ATT. In this paper, a method is exploited to solve the multi-criteria decision-making (MCDM) problems under the IFSS environment. To it, firstly, some generalized intuitionistic fuzzy soft operational laws are introduced based on ATT. Secondly, we reveal some averaging and geometric aggregation operators based on MSM operator. Further, some desirable features and particular cases of it are tested and build up with a new technique for illustrating MCDM problems. Finally, an illustration is given to exhibit the methodology and approach's supremacy is shown through a comparative study with prevailing techniques.
Mathematical Problems in Engineering, 2020
The objective of this paper is to present novel algorithms for solving the multiple attribute dec... more The objective of this paper is to present novel algorithms for solving the multiple attribute decision-making problems under the possibility intuitionistic fuzzy soft set (PIFSS) information. The prominent characteristics of the PIFSS are that it considers the membership and nonmembership degrees of each object during evaluation and their corresponding possibility degree. Keeping these features, this paper presents some new operation laws, score function, and comparison laws between the pairs of the PIFSSs. Further, we define COmplex PRoportional ASsessment (COPRAS) and weighted averaging and geometric aggregation operators to aggregate the PIFSS information into a single one. Later, we develop two algorithms based on COPRAS and aggregation operators to solve decision-making problems. In these approaches, the experts and the weights of the parameters are determined with the help of entropy and the distance measure to remove the ambiguity in the information. Finally, a numerical exam...
AIMS Mathematics, 2020
The theory of intuitionistic fuzzy soft set (IFSS) is an extension of the soft set theory which i... more The theory of intuitionistic fuzzy soft set (IFSS) is an extension of the soft set theory which is utilized to precise the deficiency, indeterminacy, and uncertainty of the evaluation while making decisions. The conspicuous characteristic of this mathematical concept is that it considers two distinctive sorts of information, namely the membership and non-membership degrees. The present paper partitioned into two folds: (i) to define the correlation measures for IFSSs; (ii) to introduce the Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS) for IFSS information. Further, few properties identified with these measures are examined thoroughly. In view of these techniques, an approach is presented to solve decision-making problems by utilizing the proposed TOPSIS method based on correlation measures. At last, an illustrative example is enlightened to demonstrate the appropriateness of the proposed approach. Also, its suitability and attainability are checked by contrasting its outcomes and the prevailing methodologies results.
Computational and Applied Mathematics, 2019
Linguistic intuitionistic fuzzy set (LIFS) is one of the effective tools to represent the data in... more Linguistic intuitionistic fuzzy set (LIFS) is one of the effective tools to represent the data in form of membership degrees in a qualitative rather than the quantitative aspects. Under this environment, the present paper develops some prioritized aggregation operators which considered the prioritized relationship between the attributes. To achieve it, first, some operational laws on LIF numbers are presented, and hence, based on these, some prioritized aggregation operators, namely, the LIF prioritized weighted, ordered weighted averaging, and geometric aggregation operators, have proposed. The fundamental properties of these operators are also investigated in detail. Furthermore, an approach to solve decision-making problem under LIFS environment has been presented and its efficiency has been verified with an illustrative example.
Journal of Ambient Intelligence and Humanized Computing, 2019
The objective of this paper is to present a Maclaurin symmetric mean (MSM) operator to aggregate ... more The objective of this paper is to present a Maclaurin symmetric mean (MSM) operator to aggregate dual hesitant fuzzy (DHF) soft numbers. The salient feature of MSM operators is that it can reflect the interrelationship between the multi-input arguments. Under DHF soft set environment, we develop some aggregation operators named as DHF soft MSM averaging (DHFSMSMA) operator, the weighted DHF soft MSM averaging (WDHFSMSMA) operator, DHF soft MSM geometric (DHFSMSMG) operator, and the weighted DHF soft MSM geometric (WDHFSMSMG) operator. Further, some properties and the special cases of these operators are discussed. Then, by utilizing these operators, we develop an approach for solving the multicriteria decision-making problem and illustrate it with a numerical example. Finally, a comparison analysis has been done to analyze the advantages of the proposed operators.
Engineering Applications of Artificial Intelligence, 2018
Intuitionistic fuzzy soft set (IFSS) theory is one of the successful extension of the soft set th... more Intuitionistic fuzzy soft set (IFSS) theory is one of the successful extension of the soft set theory to deal the uncertainty by introducing the parametrization factor during the analysis. Under this environment, the present paper develops two new scaled prioritized averaging aggregation operators by considering the interaction between the membership degrees. Further, some shortcomings of the existing operators have been highlighted and overcome by the proposed operators. The principal advantage of the operators is that they consider the priority relationships between the parameters as well as experts. Furthermore, some properties based on these operators are discussed in detail. Then, we utilized these operators to solve decision-making problem and validate it with a numerical example.
Journal of the Operational Research Society, 2018
Intuitionistic fuzzy soft set (IFSS) theory is one of the successful extensions of soft set theor... more Intuitionistic fuzzy soft set (IFSS) theory is one of the successful extensions of soft set theory for handling the uncertainty in the data by introducing the parametrisation factor during the decision-making process as compared to the existing theories. Under this IFSS environment, the present paper developed some new Bonferroni mean(BM) and weighted BM averaging operator for aggregating the different preferences of the decision-maker. Some of its desirable properties have also been discussed in details. Further, a decision-making method based on proposed operators has been presented and then illustrated with a numerical example. A comparison analysis between the proposed and the existing measures under IFSS environment has been performed in terms of counter-intuitive cases for showing the validity of it.
Scientia Iranica, 2017
Soft set theory acts as a fundamental tool for handling uncertainty in the data by adding a param... more Soft set theory acts as a fundamental tool for handling uncertainty in the data by adding a parameterization factor during the process as compared to fuzzy and intuitionistic fuzzy set theory. In the present manuscript, the work has been done under environment of the Intuitionistic Fuzzy Soft Sets (IFSSs), and some new averaging/geometric prioritized aggregation operators have been proposed whose preferences, related to attributes, are made in the form of IFSSs. Their desirable properties have also been investigated. Furthermore, based on these operators, an approach to investigating the Multi-Criteria Decision Making (MCDM) problem has been presented. The e ectiveness of these operators has been demonstrated through a case study.
Scientia Iranica, 2017
Soft set theory acts as a fundamental tool for handling the uncertainty in the data by adding a p... more Soft set theory acts as a fundamental tool for handling the uncertainty in the data by adding a parameterized factor during the process unlike fuzzy as well as intuitionistic fuzzy set theory. In this manuscript, an attempt has been made to compare two Intuitionistic Fuzzy Soft Numbers (IFSNs) and then weighted averaging and geometric aggregation operators for aggregating the di erent input arguments have been presented. Further, their various properties have been established. The e ectiveness of these operators has been demonstrated through a case study.
International Journal of Intelligent Systems, 2018
The aim of this paper is to develop some new power aggregation operators for intuitionistic fuzzy... more The aim of this paper is to develop some new power aggregation operators for intuitionistic fuzzy (IF) soft numbers. The aggregation operators are named as IF soft power averaging (IFSPA) operator, weighted IFSPA (WIFSPA) operator, ordered WIFSPA operator, IF soft power geometric (IFSPG) operator, and weighted and ordered weighted IFSPG aggregation operators. The salient features of these operators are discussed in detail. Further, these operators are extended to its generalized version and called generalized IFSPA or geometric aggregation operators. Then, we utilized these operators to develop an approach to solve the decision-making problem under IF soft set environment and demonstrated with an illustrative example. A comparative analysis of existing approaches has been done for showing the validity of the proposed work. K E Y W O R D S aggregation operator, decision-making, intuitionistic fuzzy soft set, power operator, weighted averaging or geometric aggregation operators 1 | INTRODUCTION Intuitionistic fuzzy set (IFS) theory 1 is one of the successful extension of the fuzzy set theory 2 by taking a pair of membership degrees to describe the belongings of the element into the set. In it, each element is described by its membership and nonmembership degrees such that their sum is not greater than one. The IFS has received more and more attention by the researchers since
Cognitive Computation, 2018
Soft set theory acts as a fundamental tool for handling the uncertainty in the data by adding a p... more Soft set theory acts as a fundamental tool for handling the uncertainty in the data by adding a parameterization factor during the process as compared to fuzzy and intuitionistic fuzzy set theories. Under this environment, dual hesitant fuzzy soft set (DHFSS) is one of the most successful extensions of a fuzzy soft set in which preferences are represented in terms of a set of possible values than a single number. In this paper, some new aggregation operators, namely, dual hesitant fuzzy soft weighted averaging and geometric operators proposed along with their proofs to aggregate the different preferences of the decision-makers. Various desirable properties of its are also investigated in details. Further, these aggregation operators are extended to its generalized operator by incorporating the attitude character of the decision-maker towards the data. In this study, multicriteria decision-making approach is presented based on the proposed operators for solving the decision-making problems. An illustrative example present to demonstrate the approach under DHFSS environment and compared their results with some of the existing approaches results. The proposed measures illustrate with case studies along with the effect of the different parameters on the ordering of the objects which makes the proposed operators more flexible and offers the various choices to the decision-maker for assessing the decisions. From the study, it is concluded that the proposed approach provides a more practical nature to the decision-maker during the aggregation process and hence demonstrate that they place an alternative way for solving the decision-making problems.
Engineering Applications of Artificial Intelligence, 2018
The objective of this work is to present novel correlation coefficients for measuring the relatio... more The objective of this work is to present novel correlation coefficients for measuring the relationship between two dual hesitant fuzzy soft set (DHFSSs). In the existing studies of fuzzy and intuitionistic fuzzy sets, the uncertainties which are present in the data are handled without considering the parameterizations factor of each expert during the process, which may lose some useful information of alternatives and hence affect the decision results. On the other hand, soft set theory handles the uncertainties by considering both the parameterizations as well as criteria during the evaluation of the object. Thus, motivated by this, we develop correlation coefficient and weighted correlation coefficients under the DHFSS environment in which pairs of membership, non-membership are to be considered as vector representation during the formulation and to investigate their properties. Further, under this environment, a multicriteria decision making method based on the proposed correlation coefficients are presented. Three numerical examples, one from the selection procedure and other from the medical diagnosis and pattern recognition, are taken to demonstrate the efficiency of the proposed approach and compared their results with the several existing approaches results.
Applied Intelligence, 2017
Intuitionistic fuzzy soft set (IFSS) theory acts as a fundamental tool for handling the uncertain... more Intuitionistic fuzzy soft set (IFSS) theory acts as a fundamental tool for handling the uncertainty in the data by adding a parameterizing factor during the process as compared to fuzzy and intuitionistic fuzzy set (IFS) theories. In this paper, an attempt has been made to this effect to describe the concept of generalized IFSS (GIFSS), as well as the group-based generalized intuitionistic fuzzy soft set (GGIFSS) in which the evaluation of the object is done by the group of experts rather than a single expert. Based on this information, a new weighted averaging and geometric aggregation operator has been proposed by taking the intuitionistic fuzzy parameter. Finally, a decision-making approach based on the proposed operator is being built to solve the problems under the intuitionistic fuzzy environment. An illustrative example of the selection of the optimal alternative has been given to show the developed method. Comparison analysis between the proposed and the existing operators have been performed in term of counter-intuitive cases for showing the superiority of the approach.
Applied Intelligence, 2017
Interval-valued intuitionistic fuzzy (IVIF) soft set is one of the useful extensions of the fuzzy... more Interval-valued intuitionistic fuzzy (IVIF) soft set is one of the useful extensions of the fuzzy soft set which efficiently deals with the uncertain data for the decisionmaking processes. In this paper, an attempt has been made to present a nonlinear-programming (NP) model based on the technique for order preference by similarity to ideal solution (TOPSIS), to solve multi-attribute decision-making problems. In this approach, both ratings of alternatives on attributes and weights of attributes are represented by IVIF sets. Based on the available information, NP models are constructed on the basis of the concepts of the relativecloseness coefficient and the weighted distance. Some NP models are further deduced to calculate relative-closeness of sets of alternatives which can be used to generate the ranking order of the alternatives. A real example is taken to demonstrate the applicability and validity of the proposed methodology.
Lecture notes in networks and systems, 2023
International Journal of Lightweight Materials and Manufacture
International Journal of Lightweight Materials and Manufacture, 2022
Advances in Intelligent Systems and Computing, 2019
The manuscript aims to create a few aggregation operators based on Einstein norms under intuition... more The manuscript aims to create a few aggregation operators based on Einstein norms under intuitionistic fuzzy (IF) soft set environment. For this, some operational laws based on Einstein sum and product are discussed. Then, based on these operations, Einstein averaging and geometric operators such as IF soft weighted Einstein averaging (IFSWEA) and IF soft weighted Einstein geometric (IFSWEG) operator are proposed. Further, some of their properties are investigated and the relationship between the proposed operators and the existing ones is explored. Furthermore, an approach for solving DM problems has been presented and illustrated with an example for demonstrating the effectiveness of proposed work.
Artificial Intelligence Review, 2020
Intuitionistic fuzzy soft set (IFSS) accommodates more uncertainties within the information by co... more Intuitionistic fuzzy soft set (IFSS) accommodates more uncertainties within the information by considering the parameterization feature than the intuitionistic fuzzy sets and hence its applications are more extensive. Archimedean T-conorm and T-norm (ATT), consists of T-norm and T-conorm classes, is as an essential source to make the comprehensive operational laws. Meanwhile, the Maclaurin symmetric mean (MSM) has a prominent characteristic and the advantage that it can take into account the interrelation between multi-input arguments, including different attributes or different experts. Motivated by these chief characteristics, in this article, we extend the MSM operators to the IFSS based on ATT. In this paper, a method is exploited to solve the multi-criteria decision-making (MCDM) problems under the IFSS environment. To it, firstly, some generalized intuitionistic fuzzy soft operational laws are introduced based on ATT. Secondly, we reveal some averaging and geometric aggregation operators based on MSM operator. Further, some desirable features and particular cases of it are tested and build up with a new technique for illustrating MCDM problems. Finally, an illustration is given to exhibit the methodology and approach's supremacy is shown through a comparative study with prevailing techniques.
Mathematical Problems in Engineering, 2020
The objective of this paper is to present novel algorithms for solving the multiple attribute dec... more The objective of this paper is to present novel algorithms for solving the multiple attribute decision-making problems under the possibility intuitionistic fuzzy soft set (PIFSS) information. The prominent characteristics of the PIFSS are that it considers the membership and nonmembership degrees of each object during evaluation and their corresponding possibility degree. Keeping these features, this paper presents some new operation laws, score function, and comparison laws between the pairs of the PIFSSs. Further, we define COmplex PRoportional ASsessment (COPRAS) and weighted averaging and geometric aggregation operators to aggregate the PIFSS information into a single one. Later, we develop two algorithms based on COPRAS and aggregation operators to solve decision-making problems. In these approaches, the experts and the weights of the parameters are determined with the help of entropy and the distance measure to remove the ambiguity in the information. Finally, a numerical exam...
AIMS Mathematics, 2020
The theory of intuitionistic fuzzy soft set (IFSS) is an extension of the soft set theory which i... more The theory of intuitionistic fuzzy soft set (IFSS) is an extension of the soft set theory which is utilized to precise the deficiency, indeterminacy, and uncertainty of the evaluation while making decisions. The conspicuous characteristic of this mathematical concept is that it considers two distinctive sorts of information, namely the membership and non-membership degrees. The present paper partitioned into two folds: (i) to define the correlation measures for IFSSs; (ii) to introduce the Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS) for IFSS information. Further, few properties identified with these measures are examined thoroughly. In view of these techniques, an approach is presented to solve decision-making problems by utilizing the proposed TOPSIS method based on correlation measures. At last, an illustrative example is enlightened to demonstrate the appropriateness of the proposed approach. Also, its suitability and attainability are checked by contrasting its outcomes and the prevailing methodologies results.
Computational and Applied Mathematics, 2019
Linguistic intuitionistic fuzzy set (LIFS) is one of the effective tools to represent the data in... more Linguistic intuitionistic fuzzy set (LIFS) is one of the effective tools to represent the data in form of membership degrees in a qualitative rather than the quantitative aspects. Under this environment, the present paper develops some prioritized aggregation operators which considered the prioritized relationship between the attributes. To achieve it, first, some operational laws on LIF numbers are presented, and hence, based on these, some prioritized aggregation operators, namely, the LIF prioritized weighted, ordered weighted averaging, and geometric aggregation operators, have proposed. The fundamental properties of these operators are also investigated in detail. Furthermore, an approach to solve decision-making problem under LIFS environment has been presented and its efficiency has been verified with an illustrative example.
Journal of Ambient Intelligence and Humanized Computing, 2019
The objective of this paper is to present a Maclaurin symmetric mean (MSM) operator to aggregate ... more The objective of this paper is to present a Maclaurin symmetric mean (MSM) operator to aggregate dual hesitant fuzzy (DHF) soft numbers. The salient feature of MSM operators is that it can reflect the interrelationship between the multi-input arguments. Under DHF soft set environment, we develop some aggregation operators named as DHF soft MSM averaging (DHFSMSMA) operator, the weighted DHF soft MSM averaging (WDHFSMSMA) operator, DHF soft MSM geometric (DHFSMSMG) operator, and the weighted DHF soft MSM geometric (WDHFSMSMG) operator. Further, some properties and the special cases of these operators are discussed. Then, by utilizing these operators, we develop an approach for solving the multicriteria decision-making problem and illustrate it with a numerical example. Finally, a comparison analysis has been done to analyze the advantages of the proposed operators.
Engineering Applications of Artificial Intelligence, 2018
Intuitionistic fuzzy soft set (IFSS) theory is one of the successful extension of the soft set th... more Intuitionistic fuzzy soft set (IFSS) theory is one of the successful extension of the soft set theory to deal the uncertainty by introducing the parametrization factor during the analysis. Under this environment, the present paper develops two new scaled prioritized averaging aggregation operators by considering the interaction between the membership degrees. Further, some shortcomings of the existing operators have been highlighted and overcome by the proposed operators. The principal advantage of the operators is that they consider the priority relationships between the parameters as well as experts. Furthermore, some properties based on these operators are discussed in detail. Then, we utilized these operators to solve decision-making problem and validate it with a numerical example.
Journal of the Operational Research Society, 2018
Intuitionistic fuzzy soft set (IFSS) theory is one of the successful extensions of soft set theor... more Intuitionistic fuzzy soft set (IFSS) theory is one of the successful extensions of soft set theory for handling the uncertainty in the data by introducing the parametrisation factor during the decision-making process as compared to the existing theories. Under this IFSS environment, the present paper developed some new Bonferroni mean(BM) and weighted BM averaging operator for aggregating the different preferences of the decision-maker. Some of its desirable properties have also been discussed in details. Further, a decision-making method based on proposed operators has been presented and then illustrated with a numerical example. A comparison analysis between the proposed and the existing measures under IFSS environment has been performed in terms of counter-intuitive cases for showing the validity of it.
Scientia Iranica, 2017
Soft set theory acts as a fundamental tool for handling uncertainty in the data by adding a param... more Soft set theory acts as a fundamental tool for handling uncertainty in the data by adding a parameterization factor during the process as compared to fuzzy and intuitionistic fuzzy set theory. In the present manuscript, the work has been done under environment of the Intuitionistic Fuzzy Soft Sets (IFSSs), and some new averaging/geometric prioritized aggregation operators have been proposed whose preferences, related to attributes, are made in the form of IFSSs. Their desirable properties have also been investigated. Furthermore, based on these operators, an approach to investigating the Multi-Criteria Decision Making (MCDM) problem has been presented. The e ectiveness of these operators has been demonstrated through a case study.
Scientia Iranica, 2017
Soft set theory acts as a fundamental tool for handling the uncertainty in the data by adding a p... more Soft set theory acts as a fundamental tool for handling the uncertainty in the data by adding a parameterized factor during the process unlike fuzzy as well as intuitionistic fuzzy set theory. In this manuscript, an attempt has been made to compare two Intuitionistic Fuzzy Soft Numbers (IFSNs) and then weighted averaging and geometric aggregation operators for aggregating the di erent input arguments have been presented. Further, their various properties have been established. The e ectiveness of these operators has been demonstrated through a case study.
International Journal of Intelligent Systems, 2018
The aim of this paper is to develop some new power aggregation operators for intuitionistic fuzzy... more The aim of this paper is to develop some new power aggregation operators for intuitionistic fuzzy (IF) soft numbers. The aggregation operators are named as IF soft power averaging (IFSPA) operator, weighted IFSPA (WIFSPA) operator, ordered WIFSPA operator, IF soft power geometric (IFSPG) operator, and weighted and ordered weighted IFSPG aggregation operators. The salient features of these operators are discussed in detail. Further, these operators are extended to its generalized version and called generalized IFSPA or geometric aggregation operators. Then, we utilized these operators to develop an approach to solve the decision-making problem under IF soft set environment and demonstrated with an illustrative example. A comparative analysis of existing approaches has been done for showing the validity of the proposed work. K E Y W O R D S aggregation operator, decision-making, intuitionistic fuzzy soft set, power operator, weighted averaging or geometric aggregation operators 1 | INTRODUCTION Intuitionistic fuzzy set (IFS) theory 1 is one of the successful extension of the fuzzy set theory 2 by taking a pair of membership degrees to describe the belongings of the element into the set. In it, each element is described by its membership and nonmembership degrees such that their sum is not greater than one. The IFS has received more and more attention by the researchers since
Cognitive Computation, 2018
Soft set theory acts as a fundamental tool for handling the uncertainty in the data by adding a p... more Soft set theory acts as a fundamental tool for handling the uncertainty in the data by adding a parameterization factor during the process as compared to fuzzy and intuitionistic fuzzy set theories. Under this environment, dual hesitant fuzzy soft set (DHFSS) is one of the most successful extensions of a fuzzy soft set in which preferences are represented in terms of a set of possible values than a single number. In this paper, some new aggregation operators, namely, dual hesitant fuzzy soft weighted averaging and geometric operators proposed along with their proofs to aggregate the different preferences of the decision-makers. Various desirable properties of its are also investigated in details. Further, these aggregation operators are extended to its generalized operator by incorporating the attitude character of the decision-maker towards the data. In this study, multicriteria decision-making approach is presented based on the proposed operators for solving the decision-making problems. An illustrative example present to demonstrate the approach under DHFSS environment and compared their results with some of the existing approaches results. The proposed measures illustrate with case studies along with the effect of the different parameters on the ordering of the objects which makes the proposed operators more flexible and offers the various choices to the decision-maker for assessing the decisions. From the study, it is concluded that the proposed approach provides a more practical nature to the decision-maker during the aggregation process and hence demonstrate that they place an alternative way for solving the decision-making problems.
Engineering Applications of Artificial Intelligence, 2018
The objective of this work is to present novel correlation coefficients for measuring the relatio... more The objective of this work is to present novel correlation coefficients for measuring the relationship between two dual hesitant fuzzy soft set (DHFSSs). In the existing studies of fuzzy and intuitionistic fuzzy sets, the uncertainties which are present in the data are handled without considering the parameterizations factor of each expert during the process, which may lose some useful information of alternatives and hence affect the decision results. On the other hand, soft set theory handles the uncertainties by considering both the parameterizations as well as criteria during the evaluation of the object. Thus, motivated by this, we develop correlation coefficient and weighted correlation coefficients under the DHFSS environment in which pairs of membership, non-membership are to be considered as vector representation during the formulation and to investigate their properties. Further, under this environment, a multicriteria decision making method based on the proposed correlation coefficients are presented. Three numerical examples, one from the selection procedure and other from the medical diagnosis and pattern recognition, are taken to demonstrate the efficiency of the proposed approach and compared their results with the several existing approaches results.
Applied Intelligence, 2017
Intuitionistic fuzzy soft set (IFSS) theory acts as a fundamental tool for handling the uncertain... more Intuitionistic fuzzy soft set (IFSS) theory acts as a fundamental tool for handling the uncertainty in the data by adding a parameterizing factor during the process as compared to fuzzy and intuitionistic fuzzy set (IFS) theories. In this paper, an attempt has been made to this effect to describe the concept of generalized IFSS (GIFSS), as well as the group-based generalized intuitionistic fuzzy soft set (GGIFSS) in which the evaluation of the object is done by the group of experts rather than a single expert. Based on this information, a new weighted averaging and geometric aggregation operator has been proposed by taking the intuitionistic fuzzy parameter. Finally, a decision-making approach based on the proposed operator is being built to solve the problems under the intuitionistic fuzzy environment. An illustrative example of the selection of the optimal alternative has been given to show the developed method. Comparison analysis between the proposed and the existing operators have been performed in term of counter-intuitive cases for showing the superiority of the approach.
Applied Intelligence, 2017
Interval-valued intuitionistic fuzzy (IVIF) soft set is one of the useful extensions of the fuzzy... more Interval-valued intuitionistic fuzzy (IVIF) soft set is one of the useful extensions of the fuzzy soft set which efficiently deals with the uncertain data for the decisionmaking processes. In this paper, an attempt has been made to present a nonlinear-programming (NP) model based on the technique for order preference by similarity to ideal solution (TOPSIS), to solve multi-attribute decision-making problems. In this approach, both ratings of alternatives on attributes and weights of attributes are represented by IVIF sets. Based on the available information, NP models are constructed on the basis of the concepts of the relativecloseness coefficient and the weighted distance. Some NP models are further deduced to calculate relative-closeness of sets of alternatives which can be used to generate the ranking order of the alternatives. A real example is taken to demonstrate the applicability and validity of the proposed methodology.