Teaching Period: Autumn 2009, Period II (October– December)

Subject Areas: Applied Mathematics, Operations Research, Optimization

Course Description:

The idea of this course is to give a comprehensive up-to-date survey of the approaches which are generally referred to as robust optimization. All these approaches have one feature in common – they target a situation, when problem parameters  are not deterministic, i.e. some sort of uncertainty could happen. The general idea of robust optimization is to predict possible uncertainty and construct a new problem with optimal solution being more robust, i.e. less sensitive to problem parameter variations. The course surveys the main results of robust optimization, emphasizing on modelling specific and algorithm review.

Modes of Study:: exercises, exam

Evaluation: 0-5

Teaching Methods: Lectures 28h, Home works 14h

Organization Responsible: Department of Mathematics

Person in Charge: Yury Nikulin

Further information on Study Materials:

This course is taught and evaluated in English.

Prerequisites: Basic familiarity with Linear Programming, Graph Theory and Nonlinear Optimization

Exam dates:

 

1st exam:   18.12.2009, 9a.m. Lecture Halls XXI, XXII, 4 hours

2nd exam:  05.03.2010, 9a.m. Lecture Halls IX,X, 4 hours

3rd exam:   07.05.2010, 9a.m. Lecture Halls IX,X, 4 hours
Robust Optimizationprofessor2.gif (9132 bytes)

Easy way for a student to become a professor in just one step...

”...Uncertainty is a shaky bridge separating mathematical model and reality... It is better to take care abouts its robustness in order not to stumble on the way to the target!...