Modeling and Optimization in Nutrition

ECTS points:
4

Program:
preddiplomski

Course number:
32441

Course Description

COURSE CONTENT

The module consists of the following topics: Introduction to modelling and optimisation. DRI recommendations for specific populations and individuals. Data bases of energy and nutritive contents of foods. Basics of linear programming and simplex algorithm. Recommendations for planning of meals. Paretto optimisation (multiple objective functions such as meal costs, food quality, food preferences etc.). Differences in optimisation based on age groups, gender and energy requirements. Estimation of effects of food processing conditions on nutritive content of food. Model of loss of nutritive value due to heat processing. Review of software support for optimisation, planning and analysis of nutrition. Optimisation and planning of meals, menus and new food products. Introduction to fuzzy logic planning and optimisation.

LEARNING OUTCOMES

  • define the differences in model division and differentiate data from information that are important in nutrition
  • define and describe the database on the chemical composition of the food and identify what affects the nutritional value of foods (in most cases)
  • explain the modeling of nutritional recommendation distribution curves and their statistical background and distinguish similarities and differences in nutrition planning.
  • adapt dietary recommendations to different users using computer programs (eg adjusting programs for different gender, age, physical activity, etc. based on different needs/recommendations)
  • define the basic structure of each  step in nutrition planning through the structure of the LINDO program (a goal associated with nutritional constraints) and highlight the differences in nutritional supply planning and in planning of optimal conditions for a new product
  • define and explain what are linguistic variables and why they are applied in nutrition
  • address set tasks that apply insignificance in nourishment with analysis and comparison with explicit values ​​(such as, for example, recommendations)

To enrol in this course, the following courses must be completed:

  • Mathematics
  • Basic Informatics