Modelling and Simulation in Logistics 1. Basic definitions: model and modelling types of models -continuous and discrete-event systems 2. The idea of system simulation 3. Advantages and disadvantages of system simulation 4. Main steps of a simulation study 5. Simulation examples: queuing systems nventory systems - reliability studies 6. Random events and random variables 7. Discrete random variables 8. Continuous random variables 9. Mathematical expectation and variance of a random variable 10. Examples of random variables in queuing systems, inventory systems, reliability problems 11. Examples of theoretical distributions 12. Exponential and Poison distributions 13. Empirical distributions - continuous discrete 14. Analysis of simulation results: - observation data and time-dependent data - terminating systems: - point and interval estimation of a mathematical expectation - comparison of alternative designs 15. Validation of simulation models 16. Examples of simulation applications Modelling and Simulation in Logistics 1. Basic definitions: model and modelling types of models -continuous and discrete-event systems 2. The idea of system simulation 3. Advantages and disadvantages of system simulation 4. Main steps of a simulation study 5. Simulation examples: queuing systems nventory systems - reliability studies 6. Random events and random variables 7. Discrete random variables 8. Continuous random variables 9. Mathematical expectation and variance of a random variable 10. Examples of random variables in queuing systems, inventory systems, reliability problems 11. Examples of theoretical distributions 12. Exponential and Poison distributions 13. Empirical distributions - continuous discrete 14. Analysis of simulation results: - observation data and time-dependent data - terminating systems: - point and interval estimation of a mathematical expectation - comparison of alternative designs 15. Validation of simulation models 16. Examples of simulation applications