<p>Sustainable fashion has emerged as a pressing priority in textile manufacturing, yet most existing studies fall short of addressing how recycled fibers can be systematically integrated into production while balancing cost, quality, and demand. Although prior work has emphasized the environmental and economic relevance of recycled fibers, little attention has been given to developing an operational model that simultaneously captures production constraints, market dynamics, and sustainability objectives. The objective of this study is to address this gap by developing a mathematical optimization model that determines the optimal fiber-mix composition for textile manufacturing, integrating sustainability requirements, production constraints, and demand dynamics. By explicitly discussing the trade-offs among price, quality, and marketing efforts, the study provides new insights for fiber-mix decision-making in sustainable fashion. The model integrates both the minimum required proportion of recycled fibers to support the Sustainable Development Goals (SDGs) and the operational limitations associated with higher recycled content. Computational experiments and scenario analysis demonstrate that the optimal fiber mix is 37:63 (recycled: virgin), which reduces unit price to 62% and quality to 87%, while improving sustainability and marketing factors by 30%, lowering material costs by 19%, and increasing production difficulty by 37%. These results collectively maximize demand and minimize unit total cost. The model operates under defined assumptions and is applicable within the limits of fiber spinning capabilities, sustainability requirements, and market conditions for recycled garments. The findings offer novel managerial insights and demonstrate the scientific rigor of the optimization approach for guiding sustainable textile production decisions.</p>