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Last update: G_M (16.05.2012)
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Last update: T_KPMS (25.04.2016)
The goal is to give explanation and theoretical background for standard optimization procedures. Students will learn necessary theory and practice their knowledge on numerical examples. |
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Last update: T_KPMS (25.04.2016)
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. Dupačová, J., Lachout, P.: Úvod do optimalizace. MatfyzPress, Praha, 2011. Plesník, J.; Dupačová, J.; Vlach, M.: Lineárne programovanie. Alfa, Bratislava, 1990. Rockafellar, T.: Convex Analysis. Springer-Verlag, Berlin, 1975. Wolsey, L.A.: Integer Programming, Wiley, New York, 1998. |
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Last update: T_KPMS (15.05.2012)
Lecture+exercises. |
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Last update: T_KPMS (25.04.2016)
1. Optimization problems and their formulations. Applications in economics, finance, logistics and mathematical statistics. 2. Basic parts of convex analysis (convex sets, convex multivariate functions). 3. Linear Programming (structure of the set of feasible solutions, simplex algorithm, duality, Farkas theorem). 4. Integer Linear Programming (applications, branch-and-bound algorithm). 5. Nonlinear Programming (local and global optimality conditions, constraint qualifications). 6. Quadratic Programming as a particular case of nonlinear programming problem.
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