| Summary: | Effective decision-making is critical across various domains, including technology, medicine, and engineering. To address the complexities of decision-making, particularly in scenarios involving both positive and negative parameters, this paper introduces an innovative algorithm based on weighted fuzzy soft multisets. This algorithm mitigates the issue of counterintuitive results often encountered in existing methods. By incorporating the concept of uniform fuzzy soft multisets and considering the conditional structure of these sets, our approach advances the theoretical framework of decision-making while providing a practical tool for complex scenarios. To demonstrate its practical applicability, we conduct a case study focused on selecting optimal construction materials for a building project, utilizing data from established engineering standards and a comprehensive wood properties database. The key findings of our sensitivity analysis highlight the algorithm's robustness to weight changes and adaptability to different decision sequences. These findings highlight the algorithm's potential to enhance decision support systems across various fields, such as engineering, healthcare, and environmental management. This potential is particularly valuable in complex, multi-criteria scenarios that demand nuanced, context-aware solutions.
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