Objectives and competences
- The main objective of the course is to introduce the application of discrete simulation and system dynamics at solving of the organizational problems
- Understand the methods and techniques of modeling by the principles of discrete event simulation and system dynamics
- Learn the quantitative approach to the discrete event models building and system dynamics models
- Learn the basics of simulation languages
- Study the experimental design approaches and interpretation of the results
- Conduct of the complete project in the field of discrete event simulation and system dynamics on the academic case.
Content (Syllabus outline)
- System simulation and solutions of business and organizational problems
- Discrete event simulation
- Stochastic variables and probability function
- Probability distributions and random number generation
- Uniform, exponential and empirical distribution
- Model of server systems
- Distributions of inter-arrival times and processing times
- Queuing disciplines
- Generation of inter-arrival times and processing times
- Continuous simulation and system dynamics
- Differential and difference equations in simulation
- Causal Loop Diagrams and systems’ reference mode
- Dynamical hypothesis
- Development of system dynamics models
- Data collection, statistical calculations and analysis of results
- Testing and validation of models
- Experimental design
- Introduction to agent-based models
- Modeling of micro logistic processes by cyber-physical systems
- Overview of simulation languages: FlexSim, Powersim, AnyLogic, GPSS
- Application of JavaScript programming language for development of simulation models
- Simulation examples
Learning and teaching methods
• lectures
• tutorial
Intended learning outcomes - knowledge and understanding
Knowledge and understanding:
• Quantitative modeling of management problems
• Input data analysis, preparation and statistical processing
• Definition of criterions and dynamical hypothesis testing at the solution selection
• Knowledge and ability to use simulation methods and tools, both discrete and continuous
Intended learning outcomes - transferable/key skills and other attributes
- Complete design and control of discrete and continuous processes
- Building of discrete event simulation models
- Building of system dynamics models
- Connection of the simulation models with databases and production information systems
- Harmonization of production processes
- Elimination of bottle-necks in production processes
- Analysis of structure and response of the system by the aid of system dynamics
Readings
1. Borschev A. (2013) The Big Book of Simulation Modeling: Multimethod Modeling with Anylogic 6, AnyLogic North America.
2. Gordon S.I., Guilfoos B. (2017) Introduction to Modeling and Simulation with MATLAB® and Python, Chapman and Hall/CRC.
3. Birta L.G., Arbez G. (2013) Modelling and Simulation: Exploring Dynamic System Behaviour (Simulation Foundations, Methods and Applications), Springer.
4. Zupančič B., Kunc M. A., Karba R., Modeliranje in simulacija, Fakulteta za elektrotehniko UL, 2017
5. Sterman, J. D. (2000) Business Dynamics: Systems Thinking and Modeling for a Complex World, Irwin/McGraw-Hill.
6. Severance, F. L. (2001) System Modeling and Simulation: An Introduction, John Wiley & Sons, Chichester.
Prerequisits
Basic quantitative methods and statistics
Additional information on implementation and assessment - pisni izpit
- domače naloge
- seminarska naloga
