Automated Methodology for Optimizing Menus in Personalized Nutrition

In the personalized nutrition rationalized management system the central practical task is to compile an optimized menu that provides the best value for a multi-criteria set of assessments. These are nutrient composition, cost (economic acceptability), energy value, food intolerances, individual preferences, etc. To solve the problem, a combined optimization method is used. It includes preliminary ordering of options and controlled enumeration. The result of solving the problem of developing a personalized nutrition menu is a diet that meets the needs of a particular diet, taking into account its nutritional status, individual preferences and intolerances, medical appointments. In connection with discrete values of the outputs of dishes and recipes, the task of optimizing the human diet is in practice a combinatorially integer, and for its solution the method of computer modeling and controlled enumeration of options was used. Evaluation of the effectiveness of optimization is carried out by external experts. The developed menu design system makes it possible to repeatedly solve the problem of optimizing a personalized menu when changing incoming data for reasons of changing dietary tasks, introducing new products, changing food preferences, etc. With this approach, the system is a personalized food model that is regularly used for rational planning and allows to achieve a reduction in labor costs (compared to the “manual” compilation of a menu in a computer system) by 2-3 times. An additional way to use such a model is the targeted design of functional product formulations. Moreover, the properties of the product are not evaluated in isolation, but as part of a specific diet.

@article{Karpov2019,
  title     = {Automated Methodology for Optimizing Menus in Personalized Nutrition},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {10},
  number    = {11},
  year      = {2019},
  publisher = {The Science and Information Organization},
  author    = {Valery I Karpov and Nikolay M. Portnov and Igor A. Nikitin and Yury I. Sidorenko and Sergey M. Petrov and Nadezhda M. Podgornova and Mikhail Yu. Sidorenko and Sergey V. Shterman and Igor V. Zavalishin},
  doi       = {10.14569/IJACSA.2019.0101144},
  url       = {https://doi.org/10.14569/IJACSA.2019.0101144}
}