A MATHEMATICAL MODEL FOR STUDENT ALLOWANCE AND MEALS
Abstract
ABSTRACT
This project presents a decision-support system that utilizes Linear Programming (LP) and Simultaneous Equations to optimize meal planning for university students operating within a fixed monthly budget. With a focus on nutritional balance, the study models a variety of meal combinations derived from real food data obtained from a university cafeteria. Each meal’s nutritional score was calculated using standardized caloric values for main dishes, proteins, and side items. A web-based interface was developed using HTML, CSS, and JavaScript, allowing users to input budget constraints and preferences, while the backend—developed with Flask (Python)—processed inputs and delivered optimized meal allocations.
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