MAT-60456 Optimization Methods, 5 cr

Additional information

Suitable for postgraduate studies.

Person responsible

Henri Hansen


Implementation Period Person responsible Requirements
MAT-60456 2019-01 2 Henri Hansen
Final exam + peer reviewed project work

Learning Outcomes

Modelling and solving of optimization problems Linear optimization. Nonlinear optimization with and without constraints.


Content Core content Complementary knowledge Specialist knowledge
1. Linear optimization. Simplex and dual simplex algorithms. Nonlinear optimization. Newton's method, quasi-Newton methods, gradient and conjugate gradient methods.  Karush-Kuhn-Tucker conditions.  Algorithmic considerations for optimization algorithms such as ECP.  

Study material

Type Name Author ISBN URL Additional information Examination material
Summary of lectures   Optimization methods   Timo Hämäläinen         Yes   


Course Mandatory/Advisable Description
MAT-02100 Usean muuttujan funktiot Advisable    
MAT-60000 Matriisilaskenta Advisable    

Correspondence of content

There is no equivalence with any other courses

Updated by: Hansen Henri, 01.04.2019