14263 - Mixed-Integer Programming Modulübersicht

Module Number: 14263
Module Title:Mixed-Integer Programming
  Gemischt-ganzzahlige Programmierung
Department: Faculty 1 - Mathematics, Computer Science, Physics, Electrical Engineering and Information Technology
Responsible Staff Member:
  • Prof. Dr. rer. nat. habil. Fügenschuh, Armin
Language of Teaching / Examination:English
Duration:1 semester
Frequency of Offer: On special announcement
Credits: 8
Learning Outcome:After successfully completing the module, students know the basic concepts (definitions, theorems and proofs) in the field of mixed-integer programming. They are able to formalize an applied optimization problem and solve it with mathematical means.
Contents:Polyhedron theory, estimations in integer optimization, complexity theory, totally unimodular matrices, integer polyhedra and total dual integrity, cutting planes, branch-and-bound, Lagrange Relaxations, Benders decomposition, dynamic programming, stochastic programming, column generation methods, heuristics, nonlinear mixed-integer programming, applications
Recommended Prerequisites:Knowledge in linear and mixed-integer optimization, e.g. knowledge of the content of modules
  • 13862  Optimierung und Operations Research
  • 11322  Optimierungsmethoden des Operations Research
Knowledge of the simplex algorithm is implied.
Mandatory Prerequisites:None
Forms of Teaching and Proportion:
  • Lecture / 4 Hours per Week per Semester
  • Exercise / 2 Hours per Week per Semester
  • Self organised studies / 150 Hours
Teaching Materials and Literature:Current literature will be announced or handed out in the first lecture.
Module Examination:Continuous Assessment (MCA)
Assessment Mode for Module Examination:
  • 4 intermediate tests, written during the lecture period, 30 minutes each
The best 3 count 1/3 each for the final grade.
Evaluation of Module Examination:Performance Verification – graded
Limited Number of Participants:None
Part of the Study Programme:
  • Master (research-oriented) / Mathematical Data Science / PO 2025
Remarks:
  • Study programme Mathematics M.Sc.: Compulsory elective module in complex „Optimization“
  • Study programme Mathematik B.Sc.: Compulsory elective module in complex „Vertiefung“, in limited extend 
  • Study programme Wirtschaftsmathematik B.Sc.: Compulsory elective module in complex „Vertiefung“, in limited extend
Module Components:
  • Lecture: Mixed-Integer Programming
  • Accompanying exercise
Components to be offered in the Current Semester:
  • no assignment