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Operations Research - Modeling Sustainable Mobility (OR-MSM) (Operations Research - Modeling Sustainable Mobility)



#70412 / #2

Seit SoSe 2022

Fakultät VII

H 33

Institut für Volkswirtschaftslehre und Wirtschaftsrecht

37311500 FG Volkswirtschaftlehre, insb. Wirtschafts- und Infrastrukturpolitik

Hirschhausen, Christian

Arnz, Marlin

POS-Nummer PORD-Nummer Modultitel
2350711 43669 Operations Research - Modeling Sustainable Mobility

Learning Outcomes

Transport mitigation strategies, theory of mobility behaviour analysis, advanced Python skills für transport modeling


This course starts from the challenges and relevance of decarbonizing the mobility sector in the overall energy transition and introduces respective open-source modeling approaches. Focusing on the German case, we analyze challenges of the mobility transformation, embedded within the techno-economic energy transformation in transportation. After an introduction to methods and goals of classical transport planning and transport modeling, various approaches are presented in form of open-source transport models (e.g. quetzal_germany, VencoPy). We further look at potential modeling approaches for policy effects (especially sufficiency/transportation demand policies) and examine exercises under application of various tools in Python and/or Julia. In order to analyze impacts and interplays of the mobility system evolution with the overall energy system, linkages to energy system models are explored and tested. In a subsequent term paper, students will deepen their knowledge throughout the rest of the semester in one of the topics that will be presented.

Module Components


All Courses are mandatory.

Course Name Type Number Cycle Language SWS VZ
Operations Research - Modeling Sustainable Mobility (OR-MSM) IV SS English 4

Workload and Credit Points

Operations Research - Modeling Sustainable Mobility (OR-MSM) (IV):

Workload description Multiplier Hours Total
Class attendance 15.0 4.0h 60.0h
Class preparation and follow-up 15.0 2.0h 30.0h
90.0h(~3 LP)

Course-independent workload:

Workload description Multiplier Hours Total
Preparation of paper and presentation 1.0 90.0h 90.0h
90.0h(~3 LP)
The Workload of the module sums up to 180.0 Hours. Therefore the module contains 6 Credits.

Description of Teaching and Learning Methods

Weekly course (starts in the second part of the semester), examined in small groups and comprise theoretical research as well as modeling application.

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

Advanced Python knowledge (including the following): - Functions and objects - Experience with the pandas library - Experience with Anaconda/Miniconda and virtual environments

Mandatory requirements for the module test application:

No information

Module completion



Type of exam

Portfolio examination

Type of portfolio examination

100 points in total



Test elements

Name Points Categorie Duration/Extent
Term paper 80 written max. 20 p.
Group presentation 20 oral 20 min./group

Grading scale

Test description (Module completion)

The portfolio examination consists of the following elements, adding up to a maximum of 100 credits. The grading follows the joint conversion key of the School of Economics and Management (decision of the school's council dated May 28, 2014 - FKR VII-4/8-28.05.2014).

Duration of the Module

The following number of semesters is estimated for taking and completing the module:
1 Semester.

This module may be commenced in the following semesters:

Maximum Number of Participants

The maximum capacity of students is 24.

Registration Procedures

Via email to

Recommended reading, Lecture notes

Lecture notes

Availability:  unavailable

Electronical lecture notes

Availability:  available


Recommended literature
No recommended literature given.

Assigned Degree Programs

This module is not used in any degree program.

This module is used in the following Degree Programs (new System):


No information