Recommending healthy meal plans by optimising nature-inspired many-objective diet problem

Türkmenoğlu C., Uyar A. S. E., Kiraz B.

HEALTH INFORMATICS JOURNAL, vol.27, no.1, 2021 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 27 Issue: 1
  • Publication Date: 2021
  • Doi Number: 10.1177/1460458220976719
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Applied Science & Technology Source, CINAHL, Computer & Applied Sciences, EBSCO Education Source, Educational research abstracts (ERA), EMBASE, INSPEC, Library and Information Science Abstracts, Library, Information Science & Technology Abstracts (LISTA), MEDLINE
  • Istanbul Technical University Affiliated: Yes


Healthy eating is an important issue affecting a large part of the world population, so human diets are becoming increasingly popular, especially with the devastating consequences of Coronavirus Disease (Covid-19). A realistic and sustainable diet plan can help us to have a healthy eating habit since it considers most of the expectations from a diet without any restriction. In this study, the classical diet problem has been extended in terms of modelling, data sets and solution approach. Inspired by animals' hunting strategies, it was re-modelled as a many-objective optimisation problem. In order to have realistic and applicable diet plans, cooked dishes are used. A well-known many-objective evolutionary algorithm is used to solve the diet problem. Results show that our approach can optimise specialised daily menus for different user types, depending on their preferences, age, gender and body index. Our approach can be easily adapted for users with health issues by adding new constraints and objectives. Our approach can be used individually or by dietitians as a decision support mechanism.