Food combinatorial model

Combination model to obtain an ideal list of ingredients at any time of the year through price forecasting to ensure a low price that meets nutritional requirements and tastes good.

In Mexico, according to Unicef and INEGI data, 1 in 20 children under the age of 5 and 1 in 3 children between the ages of 6 and 19 are overweight or obese. This places Mexico among the first places in childhood obesity worldwide, a problem that occurs more often in the northern states and in urban communities. 1 in 8 children under the age of 5 suffers from chronic malnutrition. Malnutrition occurs mainly in Mexico's southern states and in rural rather than urban communities; indigenous households are the most affected.

This leads to a series of more serious problems, which are chronic degenerative diseases, such as diabetes, cardiovascular conditions and a series of diverse medical ailments, as well as malnutrition generates developmental problems, in addition to mentioning the psychosocial spectrum of the infant's development.

The lack of knowledge about how to create a balanced diet with the available resources, and in the case of support programmes, how to provide more people with these balanced meals at a lower cost, all of this is based on a poor diet and lack of knowledge about how to create a balanced diet with the available resources.

A linear and integer programming model that generates an ideal food mix to meet the caloric expenditure and with a focus on the food mix having a great taste, this is achieved by incorporating aromatic particles in the model, regardless of the season of the year, always guaranteeing a low price, with a forecasting model for the food price.

The population of low and middle socio-economic level, one of the main problems these people face are medical and developmental problems, which are closely related to their nutrition and diet, giving rise to a strong public health problem, as chronic diseases such as diabetes and obesity, As a solution to this, diets and suggested dishes have been tried to meet the ideal caloric intake, but they end up being left aside due to two main factors: they do not taste good and the cost of the proposed inputs end up not being profitable for these people; Therefore, the model proposes a series of low-cost ingredients at any time of the year and that the taste is ideal, thus improving their quality of life.

Being the only member of the team, I have a strong connection with the problem, I come from a lower middle class family, my father is a chef and taught me that great love for cooking and in the end I decided to study Actuarial Science, and the experience in the area of statistics and computer development along with the culinary skills gave me the opportunity to understand, the great underlying problem of these health problems, we do not know how to eat, in broad strokes, There are thousands of food combinations for this balanced diet, what I observed in my community, Acapulco, is that although there are food substitutes and to maintain a diet, they were left aside by the lack of knowledge of the food, its potential, as well as the fact of a bad food culture, excessive consumption of certain foods, come from a family predisposition and abuse of these foods high in sugar and without nutritional value.

With all these when I realized how I could unite my sensitivity and my knowledge of food with the statistical tools of the career I managed to understand the potential of this idea, also I have complemented it with subjects such as bromatology, food chemistry, food physicochemistry and dietary calculation, to gradually build a model adjusted to the needs of the population and can learn and create better lists according to the tastes of the population, in addition to including foods not very popular in the diet of the Mexican.

The research is based purely on national statistics from INEGI and UNICEF, to see what the size of the target population is and the value of social programs aimed at this population.

The solution takes a problem that we can say is a classic dietary problem, but adds the factor of its chemical synergy for optimal taste, and low cost, additionally that we can forecast food costs, allowing us to hedge with derivatives, due to the volume of food that is purchased, as it is focused on the public sector for social support programmes.

To reduce child overweight and malnutrition statistics in Mexico by 25% in the first two years.

 Savings in social programs' food assistance spending of 10% with the use of coverage and purchase planning strategies and forecasting in the first year.

It is the implementation of deep learning and Machine Learning for food price forecasting and combination model with use of linear programming and implementation of constraints with user feedback to give better listing according to the characteristics of the target population and introduction of new foods

A total of 44 million children and youth

There is mostly a cultural aspect of how to modify eating habits that are related to different factors of opportunity and habit and convenience that can be quicker and cheaper.

The only institution I am collaborating with is the Universidad Anáhuac México, as a student I ask for consultancies with different teachers on specific project issues.

The main client is the federal governments as a consultant or an external for a better efficiency of their social support programs, in the area of food support and the other is an app where you can create your own food profile and create lists according to your restrictions and possible suggestions with your likes and dislikes.

In consulting in hotels and restaurants to generate capital and to test and improve the product so that it can be fully automated and already have the machine learning part in place.