Úvod FMEPCG 2118601


Title of the subject: Nonlinear programming

Semester_of_study (WT – winter/ST – summer): WT

Learning outcomes: The study of method for optimisation of nonlinear problems. To teach of students suitable to apply in praxes these methods.

Brief content of course: The formulation of tasks of nonlinear programing. The classification of methods. Methods of classical analysis, first and second conditions, Lagrange multiplications. Methods of optimisation of one dimensional problems (Passive finding of extreme, Fiboanacci method, Golden cut method, Quadratic interpolation optimisation method, Newton Raphson method) Methods of optimisation for vector objective functions (Passive finding of vector extreme, Relaxing methods, Rossebrock m., Simplex method). Gradient method for free extreme (Simple gradient m., Method the biggest falling gradient, Modification of algorithms for gradient m.). Method of second order for free extreme. Optimisation methods of second order to subject equations. (Gradient and Newton method). Optimisation methods of second order to subject an inequalities (Gradient m., Linear approximation m.). Methods of penalty functions.

Literature: Pardalos P. M., Resende M.G.C.: Handbook of Applied Optimization, Oxford University press, 2002