| | SLO | ENG | Cookies and privacy

Bigger font | Smaller font

Search the digital library catalog Help

Query: search in
search in
search in
search in
* old and bologna study programme

Options:
  Reset


1 - 4 / 4
First pagePrevious page1Next pageLast page
1.
2.
A COMPREHENSIVE REVIEW OF BAT ALGORITHMS AND THEIR HYBRIDIZATION
Iztok Fister, 2013, master's thesis

Abstract: Swarm intelligence is a modern and efficient mechanism for solving hard problems in computer science, engineering, mathematics, economics, medicine and optimization. Swarm intelligence is the collective behavior of decentralized and self-organized systems. This research area is a branch of artificial intelligence and could be viewed as some kind of family relationship with evolutionary computation because both communities share a lot of common characteristics. To date, a lot of swarm intelligence algorithms have been developed and applied to several real-world problems. The main focus of this thesis is devoted to the bat algorithm which is a member of the swarm intelligence community, as developed recently. In line with this, a comprehensive analysis of papers was performed tackling this algorithm. Some hybridizations of the original algorithm were proposed because the preliminary results of this algorithm regarding the optimization of benchmark functions with higher dimensions had not too promising. Extensive experiments showed that the hybridizing the original bat algorithm has beneficial effects on the results of the original bat algorithm. Finally, an experimental study was performed during which we researched for the dependence of an applied randomized method on the results of the original bat algorithm. The results of this study showed that selecting the randomized method had a crucial impact on the results of the original bat algorithm and that the bat algorithm using Levy flights is also suitable for solving the harder optimization problems.
Keywords: swarm intelligence, evolutionary computation, bat algorithm, hybridization, review
Published: 06.09.2013; Views: 2588; Downloads: 265
.pdf Full text (8,69 MB)

3.
4.
Autonomous evolutionary algorithm
Matej Šprogar, 2010, independent scientific component part or a chapter in a monograph

Keywords: algorithm, evolutionary algorithm, controlling evolution
Published: 31.05.2012; Views: 1191; Downloads: 84
URL Link to full text

Search done in 0.14 sec.
Back to top
Logos of partners University of Maribor University of Ljubljana University of Primorska University of Nova Gorica