Abstract

This article discusses a new approach to multiple attribute decision-making (MADM) based on (l1, l2, l3) neutrosophic sets (NS). This is an extension of the NS. Neuosophic weighted averaging (NWA), neutrosophic weighted geometrics (NWG), generalized neutrosophic weighted averaging (GNWA), and generalized neutrosophic weighted geometrics (GNWG) are the topics of this article. The flowchart we presented during our discussion showed an algorithm that used these operators. Numerical examples are provided for the extended Euclidean and Hamming distance measures. As part of this communication, we will also elaborate on the properties of neutrosophic sets, such as their idempotency, their boundness, their commutativity, and their monotonicity. They make it quicker, easier, and more convenient to find the best option. Thus, there is a stronger connection between (l1, l2, l3) and more precise conclusions. Some of the current models are compared with those that have been proposed in order to demonstrate their dependability and utility. The study also revealed fascinating and intriguing findings.

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