Skip to content
2000
  1. Home
  2. A-Z Publications
  3. Current Nutrition & Food Science
  4. Volume 21, Issue 1
  5. Article
Volume 21, Issue 1
  • ISSN: 1573-4013
  • E-ISSN: 2212-3881

Abstract

Background

While most healthy diets can help control the progression of disease, they can fail in the long term for many factors. Patients abandon the diet altogether after a while because it is too restrictive or the foods are unappealing; still, others engage in less physical activity because they consume fewer calories. What's more, almost all plans are based on optimization models. These models produce statistical diets offering limited choices to users, and a small substitution can call the whole diet into question.

Objective

This article develops an intelligent system for generating flexible nutritional menus that each person can adopt to their environment and dietary preferences (food availability, price, patient eating habits, .). The system implements mathematical fuzzy optimization models and constraint satisfaction programming.

Methods and Materials

First, the Moroccon foods were decomposed using fuzzy Cmeans. Next, the artificial foods, formed by the centers, were introduced into a fuzzy mathematical optimization diet model, which controlled the total glycemic load and met the World Health Organization (WHO) and Dietary Guidelines for Americans (GDA) recommendations (requirements for personalized menu). Then, we used a genetic algorithm strategy to generate optimal serving sizes and to build a nutritional menu based on the groups formed. To help patients choose customized diets, the menu was transformed into a constraint satisfaction programming model.

Results

The proposed strategy was applied to Moroccan foods, experimental results show that all diets offer a wide range of choices to users and that substitutions comply with WHO and GDA recommendations.

Conclusion

The suggested scheme has been applied to Moroccan foods; experimental findings demonstrate that all diets provide users with a wide variety of options that keeps consumers on their diet.

© 2025 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/cnf/10.2174/0115734013293555240319070046
2024-03-21
2025-06-29

  • From This Site

    /content/journals/cnf/10.2174/0115734013293555240319070046
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Diet and physical activity: A public health priority. World health organization.2021Available from : https://journals.sagepub. com/doi/pdf/10.1177/156482650402500310(Accessed on 27 March 2014).
  2. WHO and FAO announce global initiative to promote consumption of fruit and vegetables. World Health Organization.2003Available from: https://www.who.int/news/item/11-11-2003-who-and-fao-announce-global-initiative-to-promote-consumption-of-fruit-and-vegetables(Accessed on 25 August 2004).
  3. Food information to consumers: Legislation.2021Available from : https://food.ec.europa.eu/safety/labelling-and-nutrition/food-information-consumers-legislation_en(Accessed on 24 November 2017).
  4. LopezA.D. MathersC.D. EzzatiM. JamisonD.T. MurrayC.J.L. Global and regional burden of disease and risk factors, 2001: Systematic analysis of population health data.Lancet200636795241747175710.1016/S0140‑6736(06)68770‑9 16731270
     [Google Scholar]
  5. HebdenL. O’LearyF. RanganA. Singgih LieE. HiraniV. Allman-FarinelliM. Fruit consumption and adiposity status in adults: A systematic review of current evidence.Crit. Rev. Food Sci. Nutr.201757122526254010.1080/10408398.2015.1012290 26115001
     [Google Scholar]
  6. RobertH. ShmerlingM.D. When dieting doesn’t work.In: Linear Programming and Extensions Princeton University Press.Harvard Health Publishing 2020
     [Google Scholar]
  7. OreSkovié P, Kljusuri JG. Computer generated vegan menus: The importance of food composition data base choice.J. Food Compos. Anal.20153711211810.1016/j.jfca.2014.07.002
     [Google Scholar]
  8. MassetG. MonsivaisP. MaillotM. DarmonN. DrewnowskiA. Diet optimization methods can help translate dietary guidelines into a cancer prevention food plan.J. Nutr.200913981541154810.3945/jn.109.104398 19535422
     [Google Scholar]
  9. DonatiM. MenozziD. ZighettiC. RosiA. ZinettiA. ScazzinaF. Towards a sustainable diet combining economic, environmental and nutritional objectives.Appetite2016106485710.1016/j.appet.2016.02.151 26921487
     [Google Scholar]
  10. FarrokhiA. FarahbakhshR. RezazadehJ. MinervaR. Application of Internet of Things and artificial intelligence for smart fitness: A survey.Comput. Netw.202118910785910.1016/j.comnet.2021.107859
     [Google Scholar]
  11. Van MierloK. RohmerS. GerdessenJ.C. A model for composing meat replacers: Reducing the environmental impact of our food consumption pattern while retaining its nutritional value.J. Clean. Prod.201716593095010.1016/j.jclepro.2017.07.098
     [Google Scholar]
  12. TaniguchiE. Concepts of city logistics for sustainable and live able cities.Procedia Soc. Behav. Sci.201415131031710.1016/j.sbspro.2014.10.029
     [Google Scholar]
  13. KoenenM.F. BalvertM. FleurenH. Bi-objective goal programming for balancing costs vs. nutritional adequacy.Front. Nutr.20229105620510.3389/fnut.2022.1056205 36590216
     [Google Scholar]
  14. BasE. A robust optimization approach to diet problem with overall glycemic load as objective function.Appl. Math. Model.20143819-204926494010.1016/j.apm.2014.03.049
     [Google Scholar]
  15. El MoutaouakilK. AhouragA. ChakirS. Hybrid firefly genetic algorithm and integral fuzzy quadratic programming to an optimal Moroccan diet.Mathe Mod Comput202310233835010.23939/mmc2023.02.338
     [Google Scholar]
  16. El moutaouakil K, Ahourag A, Chellak S, Cheggour M, Baizri H, Bahri A. Quadratic programming and triangular numbers ranking to an optimal moroccan diet with minimal glycemic load. Statistics, Optimization &.Inf. Comput.2023111859410.19139/soic‑2310‑5070‑1541
     [Google Scholar]
  17. El MoutaouakilK. AhouragA. ChellakS. BaïzriH. CheggourM. Fuzzy deep daily nutrients requirements representation.Revu Intel Arti202236226326910.18280/ria.360210
     [Google Scholar]
  18. El MoutaouakilK. SalihaC. HichamB. Optimal fuzzy deep daily nutrients requirements representation: Application to optimal Morocco diet problem.Mathe Mod Comput20229360761510.23939/mmc2022.03.607
     [Google Scholar]
  19. O’BrienK.O. ZavaletaN. CaulfieldL.E. WenJ. AbramsS.A. Prenatal iron supplements impair zinc absorption in pregnant Peruvian women.J. Nutr.200013092251225510.1093/jn/130.9.2251 10958820
     [Google Scholar]
  20. WeaverC.M. GordonC.M. JanzK.F. The national osteoporosis foundation’s position statement on peak bone mass development and lifestyle factors: A systematic review and implementation recommendations.Osteoporos. Int.20162741281138610.1007/s00198‑015‑3440‑3 26856587
     [Google Scholar]
  21. Zimmer mann MB, Chassard C, Rohner F. The effects of iron fortification on the gut microbiotain African children: A randomized controlled trial in Cote d’Ivoire.Am. J. Clin. Nutr.2010921406141510.3945/ajcn.110.004564
     [Google Scholar]
  22. El MoutaouakilK.E. El OuissariA.E. PaladeV. Multi-objective optimization for controlling the dynamics of the diabetic population.Mathematics20231113295710.3390/math11132957
     [Google Scholar]
  23. El MoutaouakilK. PaladeV. SafouanS. CharroudA. FP-Conv-CM: Fuzzy probabilistic convolution C-Means.Mathematics2023118193110.3390/math11081931
     [Google Scholar]
  24. AhouragA El MoutaouakilK ChellakS BaizriH CheggourM Multi-criteria optimization for optimal nutrition of Moroccan diabetics:* Note: Sub-titles are not captured in Xplore and should not be used. In 2022 InternationaConference on Intelligent Systems and Computer Vision202216
     [Google Scholar]
  25. AhouragA. El MoutaouakilK. CheggourM. ChellakS. BaizriH. Multiobjective optimization to optimal moroccan diet using genetic algorithm.Intern J Eng Mode2023361677910.31534/engmod.2023.1.ri.05a
     [Google Scholar]
  26. El MoutaouakilK. SalihaC. HichamB. MounaC. Intelligent local search optimization methods to optimal morocco regime.IntechOpen202310.5772/intechopen.105600
     [Google Scholar]
  27. NamaS. SharmaS. SahaA.K. GandomiA.H. A quantum mutation-based backtracking search algorithm.Artif. Intell. Rev.20225530193073
     [Google Scholar]
  28. KimJ.H. KimK.H. YooS.H. Evaluating and ranking the mining damage prevention programs in South Korea: An application of the fuzzy set theory.Resour. Policy20227810287310.1016/j.resourpol.2022.102873
     [Google Scholar]
  29. El MoutaouakilK. CheggourS. ChellakH. Metaheuristics optimization algorithm to an optimal moroccan diet.7th Annual International Conference on Network and Information Systems for Computers (ICNISC)Guiyang, China 23-25 July202136436810.1109/ICNISC54316.2021.00072
     [Google Scholar]
  30. U.S. department of health and human services & U.S. department of agriculture. Dietary guidelines for Americans 2005.Available from: http://www.health.gov/dietaryguidelines/dga2005/document/pdf/DGA2005.pdf
  31. BasE. A three-step methodology for GI classification, GL estimation of foods by fuzzy c-means classification and fuzzy pattern recognition, and an LP-based diet model for glycaemic control.Food Res. Int.20168311310.1016/j.foodres.2016.02.009
     [Google Scholar]
/content/journals/cnf/10.2174/0115734013293555240319070046
Loading
Fuzzy Modeling to Personalized Nutritional Menu
Curr. Nutr. Food Sci. 21, 55 (2025); https://doi.org/10.2174/0115734013293555240319070046
/content/journals/cnf/10.2174/0115734013293555240319070046
/content/journals/cnf/10.2174/0115734013293555240319070046
Loading

Data & Media loading...


  • Article Type:     Research Article
Keyword(s): artificial diet; Fuzzy C-means; fuzzy logic; genetic algorithm; glycemic load; optimization

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test