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

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  • Additional Information
    • Source:
      Publisher: SAGE Publications Country of Publication: England NLM ID: 100883604 Publication Model: Print Cited Medium: Internet ISSN: 1741-2811 (Electronic) Linking ISSN: 14604582 NLM ISO Abbreviation: Health Informatics J Subsets: MEDLINE
    • Publication Information:
      Publication: London : SAGE Publications
      Original Publication: Sheffield, UK : Sheffield Academic Press, [1997-
    • Subject Terms:
      Algorithms* ; Energy Intake*; COVID-19/*epidemiology ; Diet, Healthy/*methods; Adult ; Age Factors ; Aged ; Behavioral Sciences ; Body Mass Index ; Cooking/economics ; Cooking/methods ; Diet, Healthy/psychology ; Feeding Behavior/psychology ; Female ; Food Preferences ; Humans ; Male ; SARS-CoV-2 ; Sex Factors ; Time Factors ; Vegetarians
    • Abstract:
      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.
    • Contributed Indexing:
      Keywords: behavioural science; diet problem; healthy eating; many-objective optimisation; nature-inspired optimisation
    • Publication Date:
      Date Created: 20210113 Date Completed: 20210121 Latest Revision: 20210121
    • Publication Date:
      20221213
    • Accession Number:
      10.1177/1460458220976719
    • Accession Number:
      33438501