<p>The Sustainable Development Goals address two critical issues: global warming and malnutrition. Global warming has had a significant negative impact on the quality of life and the efficiency of various productive sectors. On the other hand, undernutrition affects 9.2% of the population, equivalent to 735 million people, while 3.4 million lives are lost annually due to overweight and obesity. These figures reflect the urgency of addressing both climate change and nutrition issues to move towards sustainable and equitable development. In this context, we conducted a comprehensive update of the literature review related to sustainable diet optimization challenges. It indicates that integrating sustainability from a holistic perspective remains challenging. Furthermore, despite current product customization trends, there is a lack of incorporating multiple dietary profiles of customers to offer different menus in a single massive food service. Accordingly, we formulate a Quadratic Mixed-Integer Programming (QMIP) model for the design of sustainable menus in massive food service systems considering multiple customer food preference profiles. The quadratic formulation, which captures interactions between selected recipes, is linearized and solved using an <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\varepsilon \)</EquationSource> <EquationSource Format="MATHML"><math> <mi>ε</mi> </math></EquationSource> </InlineEquation>-constraint multi-objective approach, where <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(CO_2\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>C</mi> <msub> <mi>O</mi> <mn>2</mn> </msub> </mrow> </math></EquationSource> </InlineEquation>-eq emissions are minimized and operational compatibility across dietary profiles is enforced as a constraint. The model integrates nutritional requirements, operational constraints, cultural acceptability, and budget limitations. A real-world case study based on a large public university in Latin America illustrates the applicability of the proposed framework. The results show <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(CO_2\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>C</mi> <msub> <mi>O</mi> <mn>2</mn> </msub> </mrow> </math></EquationSource> </InlineEquation>-eq emission reductions ranging from approximately 38% to 73% relative to baseline menus, together with per-portion cost reductions of up to 20% and an increase of 7%–12% in the number of portions served, while maintaining operational compatibility. The proposed approach is readily applicable to other massive food service contexts, including hospitals, schools, and institutional canteens.</p>