Genetic algorithms in the domain of personalized nutrition

Abstract

<div lang="en" class="abs"><p class="abs_header">Abstract</p><p>Lifestyle related public health problems are common around the world. Personal nutrient guidance is a tool for promoting healthier lifestyles. Most of the applications available on the market are based on energy only, and a reliable individual assessment and guidance is given by licensed nutritionists. Nutri-Flow has a novel approach into personalized nutrition guidance with Fuzzy Expert System (FES) enhanced with Genetic Algorithms (GA) optimization. While FES assesses the foods and beverages added into a search space, GA is used to 1nd the level of intake for them. The optimization problem is to minimize the distance to ideal nutrient intake levels, and to keep the level of change in a feasible level and take into account other nutrition variables. In this study, the suitability of GA was assessed. Also, the performance the GA was evaluated and evolved. The objective function is presented, and the overall results were evaluated numerically if the system was feasible in the domain of nutrition. The nutritional aspect is not in the scope of this study.</p></div>