105.616 Operations Research This course is in all assigned curricula part of the STEOP.\$(function(){PrimeFaces.cw("Tooltip","widget_j_id_1y",{id:"j_id_1y",showEffect:"fade",hideEffect:"fade",target:"isAllSteop"});});This course is in at least 1 assigned curriculum part of the STEOP.\$(function(){PrimeFaces.cw("Tooltip","widget_j_id_20",{id:"j_id_20",showEffect:"fade",hideEffect:"fade",target:"isAnySteop"});});

2020S, UE, 1.0h, 1.5EC

Properties

• Semester hours: 1.0
• Credits: 1.5
• Type: UE Exercise

Learning outcomes

After successful completion of the course, students are able to

• model (and apply mathematical methods) in typical operational issues such as production planning, supply chains and inventory planning, performance measurement, route planning, decision theory, etc.
• distinguish between simulation models and mathematical models (descriptive versus prescriptive models)
• discuss and apply the fundamentals of graph theory and to prove selected theorems of graph theory (selected on the basis of exemplary proof approaches)
• to explain and apply important algorithms of graph theory
• model stochastic, multi-stage problem formulations in Markov chains
• calculate statistical equilibria of irreducible ergodic markov chains and thus to weigh alternative decisions or anticipated market shares
• choose adequate queuing models and calculate the characteristic measures (such as expected length of the queue) of a queuing system and use it as decision support
• sketch basic concepts, models and methods of game theory
• explain the concepture of the Column Generation Method for large scale LPs (based on the case studies).

Subject of course

Model-based decision-support, abstraction and modeling, juxtaposition of descriptive and prescriptive models, OR case studies, efficiency and productivity measurement, introduction to queuing theory, and brief portrait of graph theory and game theory.

Teaching methods

In the exercises, examples that explain, enhance, deepen and expand the lecture are treated.

Mode of examination

Immanent

First meeting on March 4, 2020, 1:10 p.m. FH HS 4

Course dates

DayTimeDateLocationDescription
Wed13:00 - 14:0004.03.2020 - 24.06.2020FH Hörsaal 4 Operations Research WM UE
Operations Research - Single appointments
DayDateTimeLocationDescription
Wed04.03.202013:00 - 14:00FH Hörsaal 4 Operations Research WM UE
Wed11.03.202013:00 - 14:00FH Hörsaal 4 Operations Research WM UE
Wed18.03.202013:00 - 14:00FH Hörsaal 4 Operations Research WM UE
Wed25.03.202013:00 - 14:00FH Hörsaal 4 Operations Research WM UE
Wed01.04.202013:00 - 14:00FH Hörsaal 4 Operations Research WM UE
Wed22.04.202013:00 - 14:00FH Hörsaal 4 Operations Research WM UE
Wed29.04.202013:00 - 14:00FH Hörsaal 4 Operations Research WM UE
Wed06.05.202013:00 - 14:00FH Hörsaal 4 Operations Research WM UE
Wed13.05.202013:00 - 14:00FH Hörsaal 4 Operations Research WM UE
Wed20.05.202013:00 - 14:00FH Hörsaal 4 Operations Research WM UE
Wed27.05.202013:00 - 14:00FH Hörsaal 4 Operations Research WM UE
Wed03.06.202013:00 - 14:00FH Hörsaal 4 Operations Research WM UE
Wed10.06.202013:00 - 14:00FH Hörsaal 4 Operations Research WM UE
Wed17.06.202013:00 - 14:00FH Hörsaal 4 Operations Research WM UE
Wed24.06.202013:00 - 14:00FH Hörsaal 4 Operations Research WM UE

Examination modalities

Students realize explanatory, illustrative and in-depth examples partly under guidance and partly independently and present them. The preparation and presentation of the examples form the basis of the assessment, short tests complement the evaluation of the achievement of the learning outcomes.

Exams

DayTimeDateRoomMode of examinationApplication timeApplication modeExam
Wed00:00 - 00:0124.06.2020 assessed04.03.2020 13:00 - 24.05.2020 23:59TISSZeugnisdatum

Course registration

Begin End Deregistration end
29.01.2020 00:00 27.04.2020 23:59 27.04.2020 23:59

Literature

No lecture notes are available.

Miscellaneous

• Attendance Required!

German