Objectives and competences
- The main objective of the course is to introduce the application of simulation at crisis management
- Understand the methods and techniques of modeling by the principles of discrete event simulation, agent-based simulation and system dynamics
- Learn the quantitative approach to build the agent-based models, discrete event models and system dynamics models
- Learn the basics of simulation languages
- Study the experimental design approaches in the case of emergency and interpretation of the results
- Conduct of the complete project in the field of agent-based simulation, discrete event simulation and system dynamics on the selected emergency response case.
Content (Syllabus outline)
- Definition of system simulation and application at crisis management
- Review of simulation methods and tools for crisis management
- Simulation in GIS
- Structure of information system for rescue mission management and simulation of rescue mission
- Preparation of simulation study schedule in the case of crisis management
- Determination of key actors and conditions
- Determination of coordination mechanisms
- Injection of critical events
- Definition of critical events
- Definition of decision points
- Case study of emergency response in the case of toxic gas emissions in the atmosphere
- Input of parameters into simulation system; location of emissions, intensity of emissions, weather conditions
- Coordination of rescue teams according to the simulation data
- Overview of simulation languages: FlexSim, Powersim, AnyLogic, GPSS
Learning and teaching methods
- lectures
- seminar
- tutorial
Intended learning outcomes - knowledge and understanding
Knowledge and understanding:
Student will demonstrate the ability of quantitative modeling of problems in the field of crisis management;
understands the use of simulation models in the event of crisis situations,
analyzes and uses simulation methods and tools in the domain of federal as well as event and agent models for modeling crisis situations.
Readings
- Law A. M. (2014) Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management
- Borschev A. (2013) The Big Book of Simulation Modeling. Multimethod Modeling with AnyLogic, AnyLogic North America
- Wilensky U., Rand W. (2015) An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo (MIT Press)
- Zupančič B., Kunc M. A., Karba R., Modeliranje in simulacija, Fakulteta za elektrotehniko UL, 2017
- Sterman, J. D. (2000) Business Dynamics: Systems Thinking and Modeling for a Complex World, Irwin/McGraw-Hill.
- Law, A., Kelton, W. D. (1999) Simulation Modeling and Analysis. McGraw-Hill.
- Severance, F. L. (2001) System Modeling and Simulation: An Introduction, John Wiley & Sons, Chichester.
Prerequisits
- Introduction to Statistics
Additional information on implementation and assessment - written exam (60 %)
- seminar (40 %)
