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 Course module: 201500372
 201500372Mathematical Optimization
 Course info
Course module201500372
Credits (ECTS)5
Course typeCourse
Language of instructionEnglish
Contact persondr. G.J. Still
E-mailg.j.still@utwente.nl
Lecturer(s)
 Lecturer dr. P.J.C. Dickinson Lecturer dr. W. Kern Lecturer dr. G.J. Still Contactperson for the course dr. G.J. Still
Starting block
 2A
Application procedureYou apply via OSIRIS Student
Registration using OSIRISYes
Learning goals
 body { font-size: 9pt; font-family: Arial } table { font-size: 9pt; font-family: Arial } After following the course the student is able to: • Explain the way  the Gauss algorithm provides a proof of  main theorems in matrix theory.   • Describe how the Fourier-Motzkin algorithm leads to a constructive proof of the  Farkas Lemma. • Explain the basis ideas behind strong duality of linear programs and the minmax theorem for matrix games. • Describe and sketch  the special  properties of convex sets and convex functions.   • Describe the theoretical basis for the  different methods for solving smooth  (unconstrained) minimization problems and explain the working of these algorithms. • To apply the theoretical results to solve concrete (exercise) problems connected with the learned topics as well as to apply the  proofs  in a modified context.
Content
 body { font-size: 9pt; font-family: Arial } table { font-size: 9pt; font-family: Arial } The course aims to provide an introduction into algorithmic principles   and fundamental ideas of linear and nonlinear  optimization.   The course enables the student to follow more advanced courses in continuous and discrete optimization. Optimization problems appear in many real life  situations. Examples are: How can we assign the frequencies in a wireless network such that the   network is used in an optimal way.  How to choose the geometry of a design such that the device is both reliable and cheap. What is the best location  for a new power plant.   The course starts with the topic of algorithmic methods for solving linear
Assumed previous knowledge
 -
Required materials
 Course materialScript: Mathematical Optimization
Recommended materials
-
Instructional modes
 Other
Tests
 Test
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