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#70412 / #2

Seit SoSe 2022


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


Hirschhausen, Christian




Fakultät VII

Institut für Volkswirtschaftslehre und Wirtschaftsrecht

37311500 FG Volkswirtschaftlehre, insb. Wirtschafts- und Infrastrukturpolitik



H 33

Arnz, Marlin


PORD-Nr.ModultitelLPBenotungPrüfungsformPNr. (POS)Modulprüfung PORDModulprüfung PNr.

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 NameTypeNumberCycleLanguageSWSVZ
Operations Research - Modeling Sustainable Mobility (OR-MSM)IVSSEnglish4

Workload and Credit Points

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

Workload descriptionMultiplierHoursTotal
90.0h(~3 LP)
Class attendance15.04.0h60.0h
Class preparation and follow-up15.02.0h30.0h

Course-independent workload:

Workload descriptionMultiplierHoursTotal
90.0h(~3 LP)
Preparation of paper and presentation1.090.0h90.0h
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

Term paper80writtenmax. 20 p.
Group presentation20oral20 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 or@wip.tu-berlin.de

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 used in the following Degree Programs (new System):

Studiengang / StuPOStuPOsVerwendungenErste VerwendungLetzte Verwendung
Industrial Economics (M. Sc.)16SoSe 2022WiSe 2022/23
Volkswirtschaftslehre (B. Sc.)23SoSe 2022WiSe 2022/23
Wirtschaftsingenieurwesen (M. Sc.)14SoSe 2022WiSe 2022/23


No information