AI-Guided, Budget-Constrained Meal Planning: Optimizing Nutrient Adequacy at Lowest Cost

This study evaluates the effectiveness of artificial intelligence (AI) algorithms—Linear Programming (LP), Genetic Algorithms (GA), and Reinforcement Learning (RL)—in generating nutritionally adequate meal plans under varying budget constraints. Utilizing real-time retail pricing data and comprehensive nutritional information, we assess each algorithm's ability to meet dietary guidelines while minimizing cost. Our findings indicate that all three algorithms can produce cost-effective, nutritionally balanced meal plans, with each exhibiting unique strengths in terms of cost efficiency, dietary diversity, and adaptability to price fluctuations.