Staff

Doctoral studies

Theme Improvement, development and implementation of derivative-free global optimization algorithms

Supervisor dr. Remigijus Paulavičius

Study time 2016 10 01–2020 09 30

Aims:

• improve and modify, existing derivative-free global optimization algorithms in purpose to quickly and accurately solve optimization problems;
• to use parallel computer systems and parallel versions of global optimization algorithms to solve higher optimization problems;
• solve practical problems with new developed algorithms;

Main problems:

1. review existing derivative-free global optimization algorithms and define the group of global optimization algorithms, which is in interest;
2. improve the existing and offer new defined class global optimization algorithms;
3. obtained results compare to the results obtained using already known global optimization algorithms;
4. offer parallel versions of global optimization algorithms;
5. adapt developed algorithms for practical problems.