MODELING AND SIMULATION

I. Elements of mathematical modeling and simulation 1. Introduction 2. Process of mathematical modeling 3. Models obtained through the translation of the problem in mathematical language 4. Simulation techniques and random numbers II. Models based on statistical techniques 1. Simple linear regression model 2. Polynomial regression model 3. Other simple regression models 4. Multiple linear regression models 5. Other multiple regression models 6. Dynamic models III. Models based on optimization techniques 1. Elements of mathematical programming 2. Transportation problems 3. Problems related to production and stocking 4. Problems of mixtures (dietary optimization, alloy mixture optimization) 5. Problems of cutting-stock 6. Problems from games theory 7. Other optimization problems IV. Deterministic models based on equations 1. Problems of populations’ dynamic 2. Deterministic models in epidemiology 3. Deterministic models in physics

• Identifying the appropriate models and methods for solving real-life problems; • Giving the interpretation of mathematical and computer science (formal) models; • Using the simulation in the study of the behavior of developed models and evaluation of results; • Embedding the formal models in specific applications in various domains.