Volume 16, Number 3

Developing a Genetic Algorithm Based Daily Calorie Recommendation System for Humans

  Authors

Rezaul Karim^1,2, Md. Badiuzzaman Biplob¹ and Mohammad Shamsul Arefin¹, ¹Chittagong University of Engineering and Technology, Bangladesh, ²University of Chittagong, Bangladesh

  Abstract

Lately, there has been an increasing fascination with employing genetic algorithms (GAs) to tackle intricate optimization issues. Genetic algorithms (GAs) draw inspiration from natural selection and have demonstrated efficacy indiscovering optimalsolutionsformanyproblems,suchasdietoptimization.This research presents a genetic algorithm (GA) approach to estimate individuals' optimal daily calorieintake. The proposed approach considers the individual's age, gender, height, weight, exercise level, and dietary limitations.In addition, it considers the nutritional composition of various dietary items. The strategy aims to create a daily meal plan that fulfils the individual's calorie requirements and supplies all necessary nutrients. The suggested technique was assessed using a dataset consisting of 100 people. The findings demonstrated that the approach successfully produced dietary regimens that satisfied the individual's specific caloric requirements and encompassed all vital elements. The technique also produced diverse and captivating food menus. Additionally, we recommend a fitness function thatassesses each suggestion's appropriateness for a given user. Ultimately, to completely comprehend the characteristics and functionality of our system, we conducted experimental research using both synthetic data and actual users with varying requirements, preferences, and ambitions.

  Keywords

Genetic Algorithms, Personalized Diets, Knowledge Graphs, Food products, Digital Nutrition