1st Optimization problems, methods of solving
2nd Analytical methods of solving one-dimensional optimization problem
3rd The method of golden section and Fibonacci method
4th Static optimization functions of several variables, types of tasks and methods of solution
5th Solving multi-dimensional optimization problem without constraints
6th Lagrange function, its determination and significance for multi-dimensional optimization tasks
7th Solving problems with multi-dimensional optical constraints with equality
8th Khun-Tucker conditions, the derivation and meaning
9th Solving multi-dimensional problems with optical constraints in the form of inequality
10th The role of linear programming and its solution, 1 and 2 role
11th Vector optimization
12th Minimizing weighted targeted FCI
13th Dynamic program. - Recurrent Bellman equation
14th Extreme control, addressing the dynamics of the closed loop control with extreme controller
15th Genetic algorithms and their applications, evolutionary optimization methods
2nd Analytical methods of solving one-dimensional optimization problem
3rd The method of golden section and Fibonacci method
4th Static optimization functions of several variables, types of tasks and methods of solution
5th Solving multi-dimensional optimization problem without constraints
6th Lagrange function, its determination and significance for multi-dimensional optimization tasks
7th Solving problems with multi-dimensional optical constraints with equality
8th Khun-Tucker conditions, the derivation and meaning
9th Solving multi-dimensional problems with optical constraints in the form of inequality
10th The role of linear programming and its solution, 1 and 2 role
11th Vector optimization
12th Minimizing weighted targeted FCI
13th Dynamic program. - Recurrent Bellman equation
14th Extreme control, addressing the dynamics of the closed loop control with extreme controller
15th Genetic algorithms and their applications, evolutionary optimization methods