A Mixed Integer Linear Programming Approach to Bridge the Gap Between Diet Plans and Realistic Menus *

Dietary patterns are provided to help individuals achieve specific health goals, such as sustainable weight loss, chronic disease management, improved nutrition, and the establishment of long-term healthy eating habits. However, implementing these patterns in real-world settings remains a challenge. While Linear Programming is widely and successfully used to define theoretical sustainable Reference Dietary Patterns (RDP), translating these optimized targets into realistic, culturally acceptable menus remains a significant operational challenge. Manual menu planning often fails to adhere strictly to RDP specifications, thereby compromising the intended nutritional and environmental benefits. To bridge this implementation gap, this study develops a Mixed Integer Linear Programming framework that transforms theoretical RDPs into practical menus. The approach is validated through a case study on the Italian diet for a two-week menu.