A Modern Strategy for the Selection of Efficacious Solar Panels at Industrial Level under an Interval-Valued Picture Fuzzy Set Hybrid Environment

Abstract

Solar panels hold a significant amount of importance at an industrial level because they contribute to environmental sustainability by reducing carbon emissions, contribute to cost savings through reduced electricity bills, provide energy independence and reliability, and serve as a long-term investment with attractive returns. One of the objectives of this research article is to address the limitations of the current score function utilized in multi-criteria decision-making (MCDM) problems within an interval-valued picture fuzzy (IVPF) environment and to present an enhanced score function. Moreover, IVPF hybrid arithmetic operators and IVPF hybrid geometric operators are introduced in this article. These operators are further thoroughly examined to identify their key characteristics. By conducting a case study, an algorithm is formulated to select the most suitable solar panel to maximize energy availability at the industrial level in the framework of the newly proposed IVPF hybrid operators. In addition, a comprehensive comparative study is conducted to demonstrate the significance and validity of recently proposed novel techniques compared with existing methods.