Decision Support System Based on Complex q -Rung Orthopair Fuzzy Rough Hamacher Aggregation Operator through Modified EDAS Method

Abstract

The best mathematical tools for combining numerous inputs into a single result are aggregation operators. The aggregation operators work to combine all of the individual evaluation values provided in a uniform form, and they are very useful for evaluating the options provided in the decision-making process. To provide a larger space for decision makers, complex $q$ -rung orthopair fuzzy rough sets can express their uncertain information. As a generalization of the algebraic operations, the Einstein $t$ -norm and $t$ -conorm, Hamacher operations have become significant in aggregation theory. The Hamacher aggregation operator’s major characteristic is that it can capture the interrelationship between several input arguments. In this article, some Hamacher aggregation operators for complex $q$ -rung orthopair fuzzy rough sets are presented. We define a complex $q$ -rung orthopair fuzzy rough Hamacher operation laws and a new score function. In addition, we propose a serious of averaging aggregation operators for complex $q$ -rung orthopair fuzzy rough set. We present the essential properties of these operators. We use the defined operators and modified EDAS (evaluation based on distance from average solution) method to propose an approach for solving a multicriteria decision making problem. To demonstrate the practicality and effectiveness of our propose model, we consider a numerical example of area selection for an arboretum. Finally, a comparison between the suggested approach with existing operators has been presented for authenticity and reliability.