Enhanced multi-attribute decision-making method to analyze renewable energy sources for sustainable transportation by synergizing the cubic set with picture fuzzy hypersoft sets.

Due to increasing environmental degradation, urban air pollution, and energy instability, the Government of Pakistan is focusing on transitioning to cleaner and more sustainable transportation options. While biofuels have often been seen as a partial substitute, their long-term environmental and economic sustainability is limited. Problems such as land use conflicts, food security concerns, and minimal carbon reduction highlight the need for a systematic shift to renewable energy sources like solar, wind, and hydropower. These alternatives offer greater sustainability, lower carbon footprints, and support Pakistan's national climate goals and energy diversification strategies. This research introduces a new approach to decision-making on green energy options using cubic picture fuzzy hypersoft sets (CPFHSSs), which effectively manage the ambiguity and complexity involved in the evaluation process. The decision-making method applies OR and AND operations of the CPFHSSs to combine expert judgments across multiple criteria, considering both optimistic and pessimistic perspectives in the final evaluation. The methodology is demonstrated through a case study based on recent official guidance to identify and rank the most suitable renewable energy sources for sustainable transportation in Pakistan.