Quantified neutrosophic set ( Q t N S )-based MCDM algorithms for sustainable material selection for anti-microbial bio-fabricated textile manufacturing

This paper proposes a modified structure for the neutrosophic set called the Quantified Neutrosophic Set (\(\mathrm{Q^{t}NS}\)) with a parameterized setting. Unlike conventional approaches, the \(\mathrm{Q^{t}NS}\) provides a quantified environment for the indeterminacy by its dependence on truthness and falsity components. This innovative approach quantifies the uncertainty and improves the assessment process via expert-guided opinions, customising it according to the specific situations in real-world decision-making scenarios. Some \(\mathrm{Q^{t}NS}\) operations along with useful characteristics are addressed. Furthermore, two algorithms, \(\mathrm{Q^{t}NS}\)UI and \(\mathrm{Q^{t}NS}\)AO, are developed for the proposed operations of union, intersection, AND, and OR based on \(\mathrm{Q^{t}NS}\). In the world of sustainable materials, biofabricated textiles are making progress. The MCDM methods based on \(\mathrm{Q^{t}NS}\) are developed for material preferences in the industry of biofabricated textiles, specifically with anti-microbial properties. The study's main purpose is to develop a novel technique to quantify and reduce the predicted uncertainties in the material preference problem for antimicrobial biofabricated textile manufacturing. For eco-conscious decision-making, our work would provide an optimised environment at the industrial level, especially for ecologically conscious textile industries, for enhanced and sustainable selection with greater accuracy.