MADM Strategy Based on Quadripartition Neutrosophic Weighted Hamacher Aggregative Operators and Entropy Weight

Quadripartition neutrosophic number is an extension of the neutrosophic set constructed for modeling situations specifically with incomplete, indeterminate, and inconsistent information. In this paper, Quadripartition Neutrosophic Weighted Hamacher Averaging Aggregative operator and Quadripartition Neutrosophic Weighted Hamacher Geometric Aggregative operator are introduced. Hamacher aggregation operators are the extension of the algebraic aggregation operators and Einstein aggregation operators, which are more general and flexible. Some essential properties such as idempotency, commutativity, monotonicity, and boundedness properties have been investigated. A new MADM strategy is developed using the proposed operators. The entropy function is used to calculate the weights of the attributes in aggregating the decision maker’s preferences. An MADM problem of COVID-19 patient’s oxygen supply is solved to demonstrate the process. In addition, a comparison is made to ensure that the proposed strategies are consistent and superior.