Hybrid multi-criteria decision-making method with a bipolar fuzzy approach and its applications to economic condition analysis

Abstract

The bipolar fuzzy set and interval-valued bipolar fuzzy set efficiently analyse real-world problems where for each input of an object, there has counter information. This study’s main objective is to lay a foundation for considering a new approach to the bipolar fuzzy hybrid operators tool applied in a realistic frame that contains uncertainties. In this view, some mixed aggregation operators, namely, the hybrid bipolar fuzzy weighted averaging geometric (H-BFWAG), hybrid bipolar fuzzy order weighted averaging geometric (H-BFOWAG), hybrid interval-valued bipolar fuzzy weighted averaging geometric (H-IVBFWAG), and hybrid interval-valued bipolar fuzzy order weighted averaging geometric (H-IVBFOWAG) operators are generated in bipolar fuzzy environment. A decision making approach is developed to build the multi-criteria decision making model. A numerical example is considered to study the different effects on various Indian economic sectors in the COVID-19 environment. Managerial implications are highlighted in between many industrial sectors on which the Indian economy depends and the country’s gross domestic product depends on their inter-relationship. This study investigates COVID-19’s impact on society and the economy in the Indian context. A comparative investigation is introduced with some pre-existing operators and the TOPSIS (technique for order of preference by similarity to ideal solution) approach to justify the proposed method.