A Linear-Programming-Based Study for Snack Selection to Minimize Sugar Intake among Middle School Students

Excessive sugar intake among teenagers has become a growing public health concern. High-sugar snacks in campus stores are a major contributor to adolescent obesity and other related health problems. This study establishes a mixed-integer linear programming model to minimize the total sugar content of snack selections for middle school students, subject to constraints on budget, energy, protein, preference, and diversity, aiming to provide a practical and acceptable strategy to choose snacks for students. An optimal solution is obtained in a real case study based on data collected from a campus store in Beijing, covering 16 types of snack and beverage products. To examine the robustness of the model, a one-factor-at-a-time sensitivity analysis is conducted. The analysis shows how changes in key parameters affect the optimal solution and reveals trade-offs between sugar control and factors such as budget, snack variety, and preference requirements. These results provide practical strategies for students to reduce sugar intake according to their priorities among taste, budget, and health.