Mixed Integer Goal Programming for Personalized Meal Optimization with User-Defined Serving Granularity

This paper proposes Mixed Integer Goal Programming (MIGP) for personalized meal optimization. The methodology addresses limitations of existing formulations by using integer variables for practical serving counts and goal programming deviations for soft nutrient targets, allowing user-defined serving granularity.