Optimization Techniques and Programming for Developing Cost-Effective and Balanced Diet Schedules for Preschoolers

Proper nutrition is important for the growth, motor and cognitive development of young children since the foods consumed determine how well-rounded a child's diet is. However, preschool menu planning is complex because it requires balancing multiple constraints such as cost, dietary guidelines, and food variety. This study introduces a computational approach to menu planning for preschools through Linear Programming (LP), Integer Programming (IP), and Binary Programming (BP). This study highlights algorithmic design, constraint modelling, and computational efficiency in solving optimization problems, rather than focusing primarily on dietary outcomes. The models were tested using Malaysian food database to evaluate both feasibility and efficiency. The findings indicate that all models successfully fulfilled the Recommended Nutrient Intakes (RNI 2017) for children aged 4 to 6, ensuring adequate levels of energy, protein, calcium, carbohydrates, and fat. In terms of cost, the LP model was the most economical at RM4.20 per day, but impractical due to fractional servings. The IP model produced a more realistic balance between cost and practicality at RM4.40 per day. The BP model generated the most diverse and implementable menus at RM5.00 per day, though at a higher cost. Overall, these optimization methods provide decision-support tools for enhancing the efficiency of preschool menu planning.