401-0647-00L  Introduction to Mathematical Optimization

SemesterAutumn Semester 2022
LecturersD. Adjiashvili
Periodicityyearly recurring course
Language of instructionEnglish


401-0647-00 VIntroduction to Mathematical Optimization2 hrs
Tue16:15-18:00HG F 5 »
D. Adjiashvili
401-0647-00 UIntroduction to Mathematical Optimization
Groups are selected in myStudies.
Wed 12-13 or Wed 16-17

The lecturer will communicate the exact lesson times of ONLINE courses.
1 hrs
Wed12:15-13:00HG D 7.2 »
16:00-17:00ON LI NE »
16:15-17:00IFW A 36 »
D. Adjiashvili

Catalogue data

AbstractIntroduction to basic techniques and problems in mathematical optimization, and their applications to a variety of problems in engineering.
ObjectiveThe goal of the course is to obtain a good understanding of some of the most fundamental mathematical optimization techniques used to solve linear programs and basic combinatorial optimization problems. The students will also practice applying the learned models to problems in engineering.
ContentTopics covered in this course include:
- Linear programming (simplex method, duality theory, shadow prices, ...).
- Basic combinatorial optimization problems (spanning trees, shortest paths, network flows, ...).
- Modelling with mathematical optimization: applications of mathematical programming in engineering.
LiteratureInformation about relevant literature will be given in the lecture.
Prerequisites / NoticeThis course is meant for students who did not already attend the course "Mathematical Optimization", which is a more advance lecture covering similar topics. Compared to "Mathematical Optimization", this course has a stronger focus on modeling and applications.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
In examination block forBachelor's Degree Programme in Computational Science and Engineering 2016; Version 27.03.2018 (Examination Block G2)
Bachelor's Degree Programme in Computational Science and Engineering 2018; Version 13.12.2022 (Examination Block G1)
Bachelor's Programme in Computational Science and Engineering 2012; Version 13.12.2016 (Examination Block G2)
ECTS credits5 credits
ExaminersD. Adjiashvili
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examinationwritten 120 minutes
Additional information on mode of examinationAn interim examination is offered some time in the middle of the semester during one of the lecture times (90 min written exam, perhaps 7th or 8th week). The interim examination is optional, so it is possible to skip it, in which case the grade in the final examination is all that counts. Definite Final = max { Final, 0.3 Interim + 0.7 Final }
Written aidsnone
If the course unit is part of an examination block, the credits are allocated for the successful completion of the whole block.
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

No public learning materials available.
Only public learning materials are listed.


401-0647-00 UIntroduction to Mathematical Optimization
Wed12:15-13:00HG D 7.2 »
Wed16:15-17:00IFW A 36 »
G-03 (Online)
Wed16:00-17:00ON LI NE »


There are no additional restrictions for the registration.

Offered in

Agricultural Sciences MasterMethods in Agricultural EconomicsWInformation
Civil Engineering MasterMajor in Transport SystemsWInformation
Civil Engineering MasterDigitalisation Specific CoursesWInformation
Computational Biology and Bioinformatics MasterTheoryWInformation
Electrical Engineering and Information Technology MasterRecommended SubjectsWInformation
Electrical Engineering and Information Technology MasterSpecialisation CoursesWInformation
Integrated Building Systems MasterSpecialised CoursesWInformation
Mechanical Engineering MasterMechanics, Materials, StructuresWInformation
Spatial Development and Infrastructure Systems MasterRecommended Electives of Master Degree ProgrammeWInformation
Spatial Development and Infrastructure Systems MasterMajor in Transport Systems and BehaviourWInformation
Computational Science and Engineering BachelorBlock G1OInformation