Multi-criteria decision making approach for solar energy implementation using N-cubic fuzzy interaction aggregation operators

The demand of electrical energy has developed considerably as the population growth and automation in factories are still increasing. The fast changing market has resulted in the intensive increase in the manufacturing activity that has further increased the energy demands of the production activities. Solar power has therefore come up as potential remedy to this demand. Nevertheless, in case of manufacturing companies, the process of choosing, installing, and maintaining appropriate solar panel systems is a complicated one particularly when several criteria and different hierarchies of decision-makers are concerned. Further, each phase in the lifecycle of a solar panel system, such as analysis, installation, operation and decommissioning should be addressed with much care. This means that the manufacturers of solar panels should have total answers to every step. In such real-life scenarios, the multiple attribute group decision-making (MAGDM) is an effective decision-making tool to deal with uncertain and imprecise information. Aggregation operators (AOs), which are some of the tools in MAGDM that are most commonly studied, can be of specific use in the integration of different types of evaluations. We consider the theory of N-cubic fuzzy sets (NCFSs) and its fundamental operations in this work, as well as introduce a new type of aggregation operators N-cubic fuzzy interaction aggregation operators (NCFIAOs) to describe the relations between different expert opinions in uncertainty. Based on the NCFS framework, the following specific averaging operators are proposed: the NCF interaction weighted average (NCFIWA), NCF interaction ordered weighted average (NCFIOWA) and NCF interaction hybrid weighted average (NCFIHWA), each having its operational laws. To illustrate the usefulness of the proposed operators in a real-life situation, we use them to approach a real solar panel selection problem, which is one of the areas of critical concern in the national energy policy and sustainable development. One of the numerical examples will be used to describe the decision-making (DM) process, and the comparative analysis with the existing AOs will prove the effectiveness, strength, and competitiveness of the suggested approaches.