Ruprecht-Karls-Universität Heidelberg
Siegel der Universität Heidelberg

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[Mixed Integer Programming] - [2015 Sommer]

Module Code
IMIP
Name
Mixed Integer Programming
Credit Points
6 LP CP
Workload
180h
Duration
ein Semester
Cycle
0
Methods Lecture 2 SWS + Exercise course 2 SWS
Objectives To become familiar with the potential of mixed-integer programming and learn how to model problems and solve them with commercial software.
Content Linear programming and duality Polyhedral theory Postoptimal analysis Mixed-integer modelling Computation of optimal solutions Polyhedral combinatorics and combinatorial polytopes Implementation of branch-and-cut algorithms Valid inequalities and cuts
Learning outcomes The participants know the modelling possibilities of (linear) mixed-integer programming, are familiar with all solution techniques, have basic knowledge of commercial solvers, are able to solve mixed-integer optimization problems, know how to model practical problems.
Prerequisitesnone
Suggested previous knowledge
Assessments Solution of 50% of the assignments and written exam
Literature z.B. Kallrath, J. and Wilson, J.M.: Business Optimisation using Mathematical Programming, Macmillan Press, 1997
Williams, H.P.: Model Building, Wiley, 1999
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