Development of optimization methods
Development of optimization methods
In addition to machine learning and the issues of collecting and processing knowledge, a separate set of problems intensively developed at the Silesian University of Technology are optimization methods inspired by biological systems, such as genetic/evolutionary algorithms, particle swarm optimization methods. These algorithms are developed in several departments, where new approaches, operators as well as implementations are developed. The following deserve special attention:
- Hybridization of the algorithms, i.e. combining many types of algorithms, including those based on the local and global search strategies
- Development of new operators and modifications to the existing ones in order to increase the efficiency of the algorithm or reduce its computational complexity
- Modification of algorithms in order to obtain the highest possible scalability when using compute clusters and supercomputers
- Modification and development of optimization algorithms for models represented with the use of fuzzy and interval numbers
- Development of multi-criteria optimization methods with the use of game theory
- Research related to the use of metamodels in bio-inspired optimization
Contact persons (email: firstname.lastname@polsl.pl):
- dr hab. inż. Wacław Kuś, prof. PŚ (ORCID)
- dr hab. inż. Witold Beluch, prof. PŚ (ORCID)
- dr hab. inż. Adam Długosz, prof. PŚ (ORCID)
- dr hab. inż. Grzegorz Dziatkiewicz, prof. PŚ (ORCID)
- dr hab. inż. Marek Paruch, prof. PŚ (ORCID)
- dr hab. inż. Sławomir Golak, prof.. PŚ (ORCID)
- dr inż. Waldemar Mucha (ORCID)
