Computational Nutrition: An Algorithm to Generate a Diet Plan to Meet Specific Nutritional Requirements

Abstract

Many methods have been proposed to generate meal plans, but most of them only consider proximates. However, the human body requires a combination of proximates and several macronutrients, micronutrients, vitamins, and minerals. Furthermore, the models designed to generate these meal plans do not take into account an individual’s specific nutritional needs. These needs are often expressed as a combination of lower bound amount (LBA), ideal amount (IA), and upper bound amount (UBA) necessary for the human body to thrive. The aim of this project is to generate an algorithm to produce a list of food items that will meet specific nutritional requirements. With the proposed algorithm, each nutrient receives a score based on the amount of nutrient contained in the food list in relation to the LBA, IA, and UBA. These scores are aggregated to give the meal plan an overall score.