5376 Operations Modelling and Decision Analysis - Interdisciplinary Research Seminar
Assoz.Prof PD Lena Silbermayr, Ph.D., Dr. Boualem Rabta, Univ.Prof. Mag.Dr. Gerald Reiner
Contact details
Weekly hours
Language of instruction
03/20/24 to 04/04/24
Registration via LPIS
Notes to the course
Day Date Time Room
Monday 04/08/24 09:00 AM - 12:30 PM D3.0.237
Tuesday 04/09/24 08:30 AM - 12:00 PM D4.0.019
Monday 04/15/24 09:00 AM - 12:30 PM D3.0.237
Thursday 04/18/24 02:00 PM - 05:30 PM D3.0.237
Tuesday 04/23/24 02:00 PM - 05:30 PM D4.0.136
Thursday 04/25/24 02:00 PM - 05:30 PM D4.0.047

Selected stochastic problems from Operations and Supply Chain Management will be introduced. Simulation models will be presented. Modelling of decision makers’ preferences, strategies, biases and their impact on operational problems will be discussed.

Part (two lectures): Discrete events simulation.

- Random numbers generation

- Building and Analysis of simulation models

- Simulation modeling of production/inventory systems and supply chain.

Part (one lecture): System Dynamics Modeling

System dynamics is a mathematical modelling technique based on systems of differential equations. These models are able to treat non-linear relationships, time delays, and closed (feedback) loops of complex systems. Fundamental principles and formal aspects of this descriptive, quantitative, empirical research method are feedback loops based on causal link, delays, and accumulations.

Part (three lectures): Combining descriptive and prescriptive decision analysis: Incorporating behavioural factors into operations models

Frequently it has been recognized that decisions made in praxis deviate from (optimal) decisions prescribed by standard operations models, i.e. there is a discrepancy between descriptive decisions and prescriptive decisions. Behavioural operations management investigates how decision makers (operations managers, participants in experiments) act and attempts to understand what behavioural biases are responsible for the observed decisions.

Learning outcomes

Part: Discrete events simulation.

Understand the basics of discrete events simulation.

Application to selected problems in OM, SCM.


Part System Dynamics Modeling:

• Understand and apply the basic principles of System Dynamics
• Apply the dynamics of growth to selected problems
• Ability to analysis and to build basic models for OM, SCM as well as actual challenges like COVIC 19.

Part Behavioural Operations:

Understand types of behavioural operations models

Discuss models with risk preferences: Nesting prescriptive models

Learn to conduct a lab experiment for behavioural inventory decisions and supply chain relationships


Attendance requirements
Attendance at the individually agreed-upon appointments is compulsory, one-time excuses are accepted.
Teaching/learning method(s)

Distance learning lectures (via MS TEAMS):

- presentations of instructors (syncronised video conferences as well as asynchronous teaching methods)

- application of tools, e.g. Vensim (system dynamics) and lab experiments

- student presentations

- Assignments: group as well as individual


Part: System Dynamics Modeling (25 points):

- group assignment (theory)

- individual assignment (pratical exercise - model building with Vensim)

Part: Simulation (25 points)

- group assignment

- individual assignment

Part: Combining descriptive and prescriptive decision analysis: Incorporating behavioural factors into operations models (50 points)

- 2 group assignments (10 points theory, 20 points data analysis of experiment)

- individual assignment (20 points discussion of a paper from literature)


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Availability of lecturer(s)

e-maill addresses are provided on

Last edited: 2023-11-14