Optimization methods
The lecture is centered around the theory of linear programming.Basic information
- Name: Optimization methods
- Code: NOPT048
- Hours per week, examination: summer semester 2/2 C+Ex
- Language: English (Czech course)
- Schedule
- Tutorial: Information on a separate page
- Year: 2015/16
Czech students
Students in Czech language are also welcomed to lectures and exercises in English. In case of interest, I would recommended to attend both lectures and exercises in English.Colleagues
Lecture
Slides from lectures and their compact version are regularly updated. Warning: Slides are only supplement materials for my lectures. These slides do not replace lecture notes or books. See literature for detail explanations of studied topics and complete proofs.Past lectures
- 1. lecture on 23.2.
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- Introduction
- Linear programming: Examples, canonical and equation form, graphical method
- Linear, affine and convex sets, hulls and combinations
- 2. lecture on 1.3.
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- Theorem: Convex hull equals the set of all convex combinations
- Linear and affine independence
- Carathéodory's theorem
- Hyperplane separation theorem
- 3. lecture on 8.3.
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- Vertices, edges, facets and faces of polyhedrons
- Minkovski-Weil theorem
- 4. lecture on 15.3.
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- Vertices and faces of polytopes
- 5. lecture on 22.3.
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- Minimal description of a polyhedron
- 6. lecture on 29.3.
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- Simplex method
- 7. lecture on 5.4.
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- Complexity of simplex method
- Duality of linear programming
- Complementary slackness
- Fourier-Motzkin elimination
- Farkas lemma
- 8. lecture on 12.4.
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- Proof of Farkas lemma
- Proof of duality
- Integer linear programming
- Branch and bound
- Rational and integral polyhedrons
- 9. lecture on 19.4.
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- Cutting plane
- Unimodularity and total unimodularity
- 10. lecture on 26.4.
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- Network flow
- Matching in graphs
- 11. lecture on 3.5.
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- Perfect matching in bipartite graphs
- Minimial-weight perfect matching in bipartite graphs
- Perfect matching in general graphs
- 12. lecture on 10.5.
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- Minimial-weight perfect matching in general graphs
- Maximal-weight matching in general graphs
- 13. lecture on 17.5.
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- Ellipsoid method
- Approximation algorithms for minimum vertex cover problem
- 14. lecture on 24.5.
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- Matroid
Examination
Students are expected to fulfill the tutorial conditions to obtain "zápočet" and to pass the exam.Literature
- A. Schrijver, Theory of linear and integer programming, John Wiley, 1986
- W.J.Cook, W.H. Cunningham W.R.Pulleyblank, A. Schrijver, Combinatorial Optimization, John Wiley, 1997
- J. Matoušek, B. Gärtner, Understanding and using linear programming, Springer, 2006.
- J. Matoušek Introduction to Discrete Geometry. ITI Series 2003-150, MFF UK, 2003