0833 Analysis and Optimization of Distribution Networks
Belma Turan, Ph.D.
Contact details
Weekly hours
Language of instruction
09/21/23 to 09/29/23
Registration via LPIS
Notes to the course
Day Date Time Room
Monday 12/18/23 03:30 PM - 06:00 PM EA.6.032
Thursday 12/21/23 03:30 PM - 06:00 PM TC.5.03
Monday 01/08/24 03:30 PM - 06:00 PM TC.4.03
Wednesday 01/10/24 03:30 PM - 06:00 PM TC.1.01 OeNB
Thursday 01/11/24 03:30 PM - 06:00 PM TC.5.01
Monday 01/15/24 03:30 PM - 06:00 PM TC.5.01
Wednesday 01/17/24 03:30 PM - 06:00 PM TC.4.01
Thursday 01/18/24 03:30 PM - 06:00 PM TC.5.01
Monday 01/22/24 10:00 AM - 01:00 PM TC.3.03
Thursday 01/25/24 03:30 PM - 06:00 PM TC.1.01 OeNB

Introduction to graph theory

Shortest Path Problem

Traveling Salesman Problem

Vehicle Routing Problem

Basics of metaheuristics

Learning outcomes

The course conveys knowledge of basic quantitative methods for solving planning problems in transport and logistics. In the course, the theoretical foundations of the respective planning methods are presented, specific examples are worked on and practical applications are shown.

In this way, students should develop a basic understanding of logistical planning problems and suitable solution methods. After successfully completing the course the participants should be able to grasp a given problem in a quantitative (linear) model, to apply methods and techniques of transport and distribution planning, to explain basic concepts of graph theory, in relation to logistic questions, such as the determination of shortest paths to set and apply selected methods and procedures of tour planning.

Attendance requirements

This semester, the course will take place in presence. Please note that your attendance at this course must be at least 80%.

If the attendance falls below 80% for students receiving partial credit, students are graded with 5 (Nicht genügend). See further:

Teaching/learning method(s)

Lectures, teamwork, case study and exercises

Additional tutorials are offered (not mandatory but highly recommended)


Case Study: 20%

In-Class Assignments: 30%

Final Exam: 50%


Lectures start punctually. In case of in-class assignments, be aware that they are most likely to take place at the beginning of a lecture. If students are absent during the in-class assignments no make-up assignments are granted.

If a student misses the final exam, he or she can repeat the exam only if he or she provides sufficient proof of the necessity of the absence (illness, accident…). If the student misses a performance assessment worth less than 50% of the grade (e.g. a mid-term quiz), opportunities to repeat the assessment can be provided optionally by the lecturers and in any case require sufficient proof for the necessity of the absence as well. See further:

Cooperation with other students on homework assignments is encouraged. However, the final write-up must be done individually. ‘Duplicate’ homework write-ups are unacceptable and will receive a score of zero. (Any homework that is late will receive a score of zero.)

The final exam has to be passed with at least 50% of maximum points (passing the final exam is mandatory for positive evaluation of this course).


Grading scale:

(1) Excellent: 90% - 100%

(2) Good: 80% - <90%

(3) Satisfactory: 70% - <80%

(4) Sufficient: 60% - <70%

(5) Fail: <60%

Prerequisites for participation and waiting lists

Admission for the SBWL is done by the institute for transport and logistics management:

Additional questions related to Admission, please refer to


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Recommended previous knowledge and skills

The previous completion of a course introducing linear and integer programming is recommended for the participation in this course

Availability of lecturer(s)

Per email and after the session


For simplified communication please register at:

There is a facebook-group:

We recommend the speaker series of the Research Institute for Supply Chain Management:

Last edited: 2023-11-08