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Optimization in economy and statistics, introduction to
non-linear programming, theory of linear programming
with respect to convex analysis and general optimization,
overview of available optimization software, matrix games.
The contents of the course and seminar is organized so
that the lecture could be attended without the seminar.
Last update: Zichová Jitka, RNDr., Dr. (02.05.2018)
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To give explanation and theoretical background for standard optimization procedures. Students will lern necessary theory and practice their knowladge on numerical examples. Last update: T_KPMS (14.05.2013)
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Bazaraa, M.S.; Sherali, H.D.; Shetty, C.M.: Nonlinear programming: theory and algorithms. Wiley, New York, 1993.
Bertsekas, D.P.: Nonlinear programming. Athena Scientific, Belmont, 1999.
Dantzig, G.B.; Thapa, M.N.: Linear programming. 1,2. Springer, New York, 1997.
Luenberger, D.G.; Ye, Y.: Linear and Nonlinear Programming. 3rd edition, Springer, New York, 2008.
Plesník, J.; Dupačová, J.; Vlach, M.: Lineárne programovanie. Alfa, Bratislava, 1990.
Rockafellar, T.: Convex Analysis. Springer-Verlag, Berlin, 1975.
Rockafellar, T.; Wets, R. J.-B.: Variational Analysis. Springer-Verlag, Berlin, 1998.
Last update: T_KPMS (20.04.2015)
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Lecture + exercises. Last update: T_KPMS (14.05.2013)
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1. Optimisation problems and their formulations. Application in statistics a economy.
2. Selected parts of convex analyses (convex cones, separation theorems, convex function, epigraph, subdifferential).
3. Theory of nonlinear programming. (Karush-Kuhn-Tucker optimality condition, constraints qualifications).
4. Linear a convex programming like a particular case of nonlinear programming.
5. Introduction in nonsmooth optimisation (tangent and normal cone, Clark constraints qualification).
6. Introduction in game theory (games of two players with zero sum, minimax theorem). Last update: Lachout Petr, doc. RNDr., CSc. (27.04.2018)
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