The objective of this study is to introduce some covariance ordered weighted logarithmic averaging (Cov-OWLA) operators . Covariance measures the conduct of one variable based on the behavior of another;this character...
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The objective of this study is to introduce some covariance ordered weighted logarithmic averaging (Cov-OWLA) operators . Covariance measures the conduct of one variable based on the behavior of another;this characteristic makes it key for decision-making processes, especially when applied in uncertain environments. We present some families and particular cases of the introduced operators, including their generalized, induced, and generalized induced formulations. An illustrative example using real-world data on tourism gross domestic product and homeland security indicators is proposed. The results show that there was a positive linear relation between the introduced variables. In this scenario, crime did not affect tourist activity, but tourist activity incited crime. The resulting aggregation with Cov-OWLA operators shows a generally better fit when compared to traditional methods.
This paper presents the induced generalized ordered weighted logarithmicaggregation (IGOWLA) operator, this operator is an extension of the generalized ordered weighted logarithmicaggregation (GOWLA) operator. It us...
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This paper presents the induced generalized ordered weighted logarithmicaggregation (IGOWLA) operator, this operator is an extension of the generalized ordered weighted logarithmicaggregation (GOWLA) operator. It uses order-induced variables that modify the reordering process of the arguments included in the aggregation. The principal advantage of the introduced induced mechanism is the consideration of highly complex attitude from the decision makers. We study some families of the IGOWLA operator as measures for the characterization of the weighting vector. This paper presents the general formulation of the operator and some special cases, including the induced ordered weighted logarithmic geometric averaging (IOWLGA) operator and the induced ordered weighted logarithmicaggregation (IOWLA). Further generalizations using quasi-arithmetic mean are also proposed. Finally, an illustrative example of a group decision-making procedure using a multi-person analysis and the IGOWLA operator in the area of innovation management is analyzed.
The Hamming distance is a well-known measure that is designed to provide insights into the similarity between two strings of information. In this study, we use the Hamming distance, the optimal deviation model, and th...
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The Hamming distance is a well-known measure that is designed to provide insights into the similarity between two strings of information. In this study, we use the Hamming distance, the optimal deviation model, and the generalized ordered weighted logarithmic averaging (GOWLA) operator to develop the ordered weighted logarithmic averaging distance (OWLAD) operator and the generalized ordered weighted logarithmic averaging distance (GOWLAD) operator. The main advantage of these operators is the possibility of modeling a wider range of complex representations of problems under the assumption of an ideal possibility. We study the main properties, alternative formulations, and families of the proposed operators. We analyze multiple classical measures to characterize the weighting vector and propose alternatives to deal with the logarithmic properties of the operators. Furthermore, we present generalizations of the operators, which are obtained by studying their weighting vectors and the lambda parameter. Finally, an illustrative example regarding innovation project management measurement is proposed, in which a multi-expert analysis and several of the newly introduced operators are utilized.
We present the induced generalized ordered weighted logarithmicaggregation (IGOWLA) operator. It is an extension of the generalized ordered weighted logarithmicaggregation (GOWLA) operator. The IGOWLA operator uses ...
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ISBN:
(纸本)9781509042401
We present the induced generalized ordered weighted logarithmicaggregation (IGOWLA) operator. It is an extension of the generalized ordered weighted logarithmicaggregation (GOWLA) operator. The IGOWLA operator uses order-induced variables that modify the reordering mechanism of the arguments to be aggregated. The main advantage of the induced process is the consideration of the complex attitude of the decision makers. We study some properties of the IGOWLA operator, such as idempotency, commutativity, boundedness and monotonicity. Finally we present an illustrative example of a group decision-making procedure using a multi-person analysis and the IGOWLA operator in the area of innovation management.
We present the induced generalized ordered weighted logarithmicaggregation (IGOWLA) operator. It is an extension of the generalized ordered weighted logarithmicaggregation (GOWLA) operator. The IGOWLA operator uses ...
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ISBN:
(纸本)9781509042418
We present the induced generalized ordered weighted logarithmicaggregation (IGOWLA) operator. It is an extension of the generalized ordered weighted logarithmicaggregation (GOWLA) operator. The IGOWLA operator uses order-induced variables that modify the reordering mechanism of the arguments to be aggregated. The main advantage of the induced process is the consideration of the complex attitude of the decision makers. We study some properties of the IGOWLA operator, such as idempotency, commutativity, boundedness and monotonicity. Finally we present an illustrative example of a group decision-making procedure using a multi-person analysis and the IGOWLA operator in the area of innovation management.
In this article, we introduce logarithmic operations on bipolar fuzzy numbers (BFNs). We present some new operators based on these operations, namely, the logarithm bipolar fuzzy weighted averaging (L-BFWA) operator, ...
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In this article, we introduce logarithmic operations on bipolar fuzzy numbers (BFNs). We present some new operators based on these operations, namely, the logarithm bipolar fuzzy weighted averaging (L-BFWA) operator, logarithm bipolar fuzzy ordered weighted averaging (L-BFOWA) operator, and logarithm bipolar fuzzy weighted geometric (L-BFWG) operator, and logarithm bipolar fuzzy ordered weighted geometric (L-BFOWG) operator. Further, develop a multi-attribute group decision-making (MAGDM) methodology model based on logarithm bipolar fuzzy weighted averaging operator and logarithm bipolar fuzzy weighted geometric operators. To justify the proposed model's efficiency, MABAC (the multiple attribute border approximation area comparison) methods are applied to construct MAGDM with BFNs established on proposed operators. To demonstrate the proposed approach's materiality and efficiency, use the proposed method to solve supply chain management by considering numerical examples for supplier selection. The selection of suppliers is investigated by aggregationoperators to verify the MABAC technique. The presented method is likened to some existing accumulation operators to study the feasibility and applicability of the proposed model. We concluded that the proposed model is accurate, effective, and reliable.
Covariance as a measurement of dispersion allows knowing the behavior of one variable based on another. Its characteristic mechanism makes it a basic component in decision-making processes. This paper introduces some ...
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ISBN:
(纸本)9781728125473
Covariance as a measurement of dispersion allows knowing the behavior of one variable based on another. Its characteristic mechanism makes it a basic component in decision-making processes. This paper introduces some covariance logarithmic aggregation operators including the covariance generalized weighted logarithmicaggregation (Cov-GWLA) operator, the generalized covariance ordered weighted logarithmicaggregation (Coe-GOWLA) operator, the covariance ordered weighted logarithmicaggregation (Cov-OWLA) operator, the induced generalized covariance ordered weighted logarithmicaggregation (Cov-IGOWLA) operator and the induced covariance ordered weighted logarithmicaggregation (Cov-IOWLA) operator. The introduced tools extend the available information when using logarithmic aggregation operators, thus aiding decision and policy makers in the analysis of complex phenomena.
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