Prioritizing sustainable energy strategies using multi-criteria decision-making models in Type-2 Neutrosophic environment

Abstract

Emphasis on developing sustainable energy strategies is very important for the energy sector to meet its environmental, economic, and social goals. Energy policy mostly considers the need to improve energy efficiency, cut down on carbon emissions, as well as create a profitable market. One of the major problems faced by decision makers is the complication and multi dimensionality of the decision- making process with regard to assessments, which entails numerous decision criteria. Overlooking these complicating factors has the potential of creating huge bottlenecks such as prolonged energy transition timelines, cost overruns, and derailing of environmental targets. This research introduces an approach based on Type-2 Neutrosophic Fuzzy Sets to rank sustainable energy strategies, using Logarithmic Percentage Change based on Objective Weights (LOPCOW) and Ranking of Alternatives through Functional Mapping of Criterion Sub-Intervals into Single Intervals (RAFSI) methods. The proposed model seeks to improve the effectiveness and efficiency of multi-criteria decision-making model in the areas where decision making is characterized by uncertainty and incompleteness. Energy strategies are evaluated in a comprehensive manner along numerous dimensions, including ecological, economic, technological, as well as societal. This approach helps to identify strategies that effectively support the sustainable development objectives of the energy sector. The analysis indicates that prioritizing Research and Development (R&D) strategies is particularly beneficial in achieving these goals.