Abstract
This study aims to develop a linear programming optimization model that will effectively assist dietitians in preparing a meal plan for adults with the variety of foods that include appropriate food group proportion and at the same time meets his/her total daily energy requirement, macronutrients and micronutrients needs. The objective function of the programming model is designed to minimize food cost. The model was solved by Particle Swarm Optimization written in Matlab. As a result, a low-cost meal for a day was selected.
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References
DFID: Scaling Up Nutrition: The UK’s position paper on undernutrition (2011)
World Health Organization: WHO—Obesity and overweight, WHO (2017). http://www.who.int/mediacentre/factsheets/fs311/en/
Fanzo, J.: Ethical issues for human nutrition in the context of global food security and sustainable development. Glob. Food Secur. 7, 15–23 (2015)
Chan, R.S.M., Woo, J.: Prevention of overweight and obesity: how effective is the current public health approach. Int. J. Environ. Res. Public Health 7(3), 765–783 (2010)
International Food Policy Research Institute (IFPRI): Global Nutrition Report 2016 From Promise to Impact Ending Malnutrition by 2030 Summary (2016)
Schaynová, L.: A nutrition adviser’s menu planning for a client using a linear optimization model. Acta Polytech. Hung. 14(5), 121–137 (2017)
Saghir Ahmad, K.Y.: Malnutrition: causes and strategies. J. Food Process. Technol. 6(434), 2 (2015)
Food and Nutrition Research Institution-Department of Science and Technology: The Double Burden of Malnutrition in the Philippines (2016)
National Nutrition Council-NCR: 8th National Nutrition Survey reveals increasing number of overweights in Metro Manila (2016)
Dahly, D.L., Gordon-Larsen, P., Popkin, B.M., Kaufman, J.S., Adair, L.S.: Associations between multiple indicators of socioeconomic status and obesity in young adult Filipinos vary by gender, urbanicity, and indicator used. J. Nutr. 140(2), 366–370 (2010)
Roberto, Z.-F., Alexis, P.-N.: Diet generator using genetic algorithms. Res. Comput. Sci. 75, 71–77 (2014)
Ferrero, F., Hsieh, E., Wagner, A.: Diet Optimization Problem IEMS 310 Professor Armbruster Spring 2009 (2009)
Maillot, M., Darmon, N., Drewnowski, A.: Are the lowest-cost healthful food plans culturally and socially acceptable? Public Health Nutr. 13(08), 1178–1185 (2010)
Kahraman, A., Seven, H.A.: Healthy daily meal planner. In: Proceedings of the 7th Annual Workshop on Genetic Evolutionary Computation, pp. 390–393 (2005)
Pasic, M., Catovic, A., Bijelonja, I., Bathanovic, A.: Goal programming nutrition optimization model. In: Katalinic, B. (ed.), vol. 23(1), pp. 243–246 (2012)
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)
Leung, P., Wanitprapha, K., Quinn, L.A.: A recipe-based, diet-planning modelling system. Br. J. Nutr. 74(2), 151–62 (1995)
Sklan, D., Dariel, I.: Diet planning for humans using mixed-integer linear programming. Br. J. Nutr. 70(01), 27–35 (1993)
Kaldirim, E.: Application of a multi-objective genetic algorithm to the modified diet problem. Comput. Eng. 10–13 (2006)
Levine, E., Abbatangelo-Gray, J., Mobley, A., McLaughlin, G., Herzog, J.: Evaluating MyPlate: an expanded framework using traditional and nontraditional metrics for assessing health communication campaigns. J. Nutr. Educ. Behav. 44, S2–S12 (2012)
Bonito, S., Dones, L.B.: A training manual for health workers for the prevention and control of noncommunicable diseases (2009)
Pop, C.B., Chifu, V.R., Salomie, I., Cozac, A., Mesaros, I.: Particle swarm optimization-based method for generating healthy lifestyle recommendations. In: Proceedings - 2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing, ICCP 2013, pp. 15–21 (2013)
Xu, X., Rong, H., Trovati, M., Liptrott, M., Bessis, N.: CS-PSO: chaotic particle swarm optimization algorithm for solving combinatorial optimization problems. Soft Comput. 3, 1–13 (2016)
Food and Nutrition Research Institution-Department of Science and Technology: Recommended Energy Intakes per day Acceptable Macronutrient Distribution Ranges Recommended Nutrient Intakes per day ( Macronutrients) (2015)
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Porras, E., Fajardo, A., Medina, R. (2018). An Adequate Dietary Planning Model Using Particle Swarm Optimization. In: Kaenampornpan, M., Malaka, R., Nguyen, D., Schwind, N. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2018. Lecture Notes in Computer Science(), vol 11248. Springer, Cham. https://doi.org/10.1007/978-3-030-03014-8_23
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