Abstract
The menu planning helps person to keep his/her body healthy. This problem is developing in order to obtain nutritious meals within the constraint of the nutrients requirement. Therefore, planning a diet menu develops a nutritional adviser’s work and avoids errors when preparing a diet plan manually. Though, several researchers used different methods for gotten good solution. In this context, this paper elaborates a Systematic Literature Review (SLR) to select the most outstanding studies that address the Menu Planning Problem (MPP) and to classify them according to the to the three following criteria: the used methods, types of patients and the required constraints. At first, a set of 4165 studies was selected. After applying the SLR’s guidelines, this collection was filtered to 13 studies using specific inclusion and exclusion criteria as well as an accurate analysis of each study. Finally, data synthesis and new perspectives for future works are incorporated in the closing section.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Chifu, V.R., Pop, C.B., Birladeanu, A., Dragoi, N., Salomie, I.: Choice function-based constructive hyper-heuristic for generating personalized healthy menu recommendations. In: 2018 IEEE 14th International Conference on Intelligent Computer Communication and Processing (ICCP), pp. 111–118. IEEE (2018)
Kitchenham, B., Charters, S.: Guidelines for performing systematic literature reviews in software engineering (2007)
Perl Pirički, A., Magdić, D., Adam Perl, M., Žihlavski, I.: Diet optimization for overweight cardiovascular patients by simplex algorithm. In: Proceedings of Central European Congress of Food Technologists, Biotechnologists and Nutricionists, p. 383 (2008)
Husain, W., Wei, L.J., Cheng, S.L., Zakaria, N.: Application of data mining techniques in a personalized diet recommendation system for cancer patients. In: 2011 IEEE Colloquium on Humanities, Science and Engineering, pp. 239–244. IEEE (2011)
Ducrot, P., et al.: Meal planning is associated with food variety, diet quality and body weight status in a large sample of French adults. Int. J. Behav. Nutrit. Phys. Act. 14(1), 1–12 (2017)
Pop, C.B., Chifu, V.R., Salomie, I., Cozac, A., Mesaros, I.: Particle swarm optimization-based method for generating healthy lifestyle recommendations. In: 2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP), pp. 15–21. IEEE (2013)
Ahmad, N., Sani, N.S.A., Zaidi, N.M.: Optimal diet selection for university students using integer linear programming. In: AIP Conference Proceedings, vol. 2138, no. 1, p. 040002. AIP Publishing LLC (2019)
Sapri, N.S.M., Bedi, M.R.B.A.D.S., Abdul-Rahman, S., Benjamin, A.M.: A diet recommendation for diabetic patients using integer programming. In: AIP Conference Proceedings, vol. 2138, no. 1, p. 040022. AIP Publishing LLC (2019)
Hui, L.S., Sufahani, S.: Healthy menu scheduling for high blood pressure patient with optimization method through integer programming. In: Advances in Computing and Intelligent System, vol. 1, no. 1 (2019)
Hadzhikolev, E., Hadzhikoleva, S.: Application of the simplex method to create a weekly menu planner. Acta Universitatis Cinbinesis Ser. E Food Technol. 22(2) (2018)
Jridi, I., Jerbi, B., Kamoun, H.: Menu planning with a dynamic goal programming approach. Multiple Criteria Decis. Making 13, 74–87 (2018)
Schaynová, L.: A nutrition adviser’s menu planning for a client using a linear optimization model. Acta Polytechnica Hungarica 14(5), 121–137 (2017)
Ali, M., Sufahani, S., Ismail, Z.: A new diet scheduling model for Malaysian school children using zero-one optimization approach. Glob. J. Pure Appl. Math. 12(1), 413–419 (2016)
De Carvalho, I.S.T., Granfeldt, Y., Dejmek, P., Håkansson, A.: From diets to foods: using linear programming to formulate a nutritious, minimum-cost porridge mix for children aged 1 to 2 years. Food Nutr. Bull. 36(1), 75–85 (2015)
Moldovan, D.: Diet generator for elders using cat swarm optimization and wolf search. In: International Conference on Advancements of Medicine and Health Care through Technology; 12th–15th October 2016, Cluj-Napoca, Romania, pp. 238–243. Springer (2017)
Chifu, V., Bonta, R., Chifu, E.S., Salomie, I., Moldovan, D.: Particle swarm optimization based method for personalized menu recommendations. In: International Conference on Advancements of Medicine and Health Care through Technology; 12th-15th October 2016, Cluj-Napoca, Romania, pp. 232–237. Springer (2017)
Fister, D., Fister, I., Rauter, S.: Generating eating plans for athletes using the particle swarm optimization. In: 2016 IEEE 17th International Symposium on Computational Intelligence and Informatics (CINTI), pp. 000 193–000 198. IEEE (2016)
Segismundo, M.I.V., Comendador, B.E.V.: Prenatal nutrition diet generator utilizing modified genetic algorithm for smartphone. J. Autom. Control Eng. 3(1) (2015)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Kallel, D., Kanoun, I., Dhouib, D. (2022). The Menu Planning Problem: A Systematic Literature Review. In: Abraham, A., Gandhi, N., Hanne, T., Hong, TP., Nogueira Rios, T., Ding, W. (eds) Intelligent Systems Design and Applications. ISDA 2021. Lecture Notes in Networks and Systems, vol 418. Springer, Cham. https://doi.org/10.1007/978-3-030-96308-8_122
Download citation
DOI: https://doi.org/10.1007/978-3-030-96308-8_122
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-96307-1
Online ISBN: 978-3-030-96308-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)