An Integer Linear Programming Model for Optimal Food Combinations to Reach the Average Protein Intake of Student Athletes at a Least Cost

Nutrient requirements increase as a person grows to adolescence and in the context of athletes, they should maximize their dietary protein intake for effective recovery and adaptation. In fact, many athletes and coaches state that high-intensity training creates a greater protein requirement. However, it is reported that there are currently no definite guidelines for an "optimal" protein intake that supports the development of student-athletes. This study aims to optimize the average protein intake of student-athletes by collecting locally available protein-rich food and identifying the most effective food combination at the least cost utilizing a linear programming model. The data was collected through conducting a survey using a three-day food diary to collect what and how much food they consumed. Results show the optimality of protein in all of the food combinations while being able to provide a meal plan at the lowest possible cost. The lowest menu cost for breakfast was PHP 28.5, lunch with PHP 47.00, snacks with PHP 26.59, and dinner with PHP 38.2.

Keywords: linear programming, protein intake, student-athletes

Corresponding author's email: p.f.balabag@gmail.com