AI-Guided, Budget-Constrained Meal Planning: Optimizing Nutrient Adequacy at Lowest Cost
Year: 2025
Type: article
Abstract: 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.
Authors: Plotnikova, Natalya, Bocharov, Andrey
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
SDG: Zero hunger
Open Access status: green
OpenAlex ID: W6893284739
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