Pokročilé metody nature-inspired optimalizačních algoritmů a HPC implementace pro řešení reálných aplikací

The scientific aim of the project is to design advanced evolutionary algorithms
(EA) that are applicable in the up to date complex engineering optimizing and
designing problems. Another objective is to adapt such algorithms for different
user-defined platforms, e.g. for powerful GPU (Graphic Processing Unit) or, on
the other hand, for low-power embedded systems. The project is divided into three
solution phases called Work Packages (WP1-3). Within the first phase, new and
hybrid evolutionary algorithms will be designed and evaluated. The
implementations of HPC (High Performance Computing) and embedded systems will be
realized in the second phase, where the pre-defined efficiency (computational
performance, scalability, energy efficiency) will be emphasized. Within the third
phase, the practical applications, referred to as the case studies consequently,
will be elaborated. This final phase will prove the efficiency of the proposed
algorithms and practical applicability w.r.t. the predefined real tasks. The
integration objective of the project is to evolve the existing international
co-operation and establish new collaboration of the research teams within BUT
working on evolutionary algorithms with leading scientific institutions abroad.
The aim is to present common publications containing new scientific results.