3.
A COMPREHENSIVE REVIEW OF BAT ALGORITHMS AND THEIR HYBRIDIZATIONIztok Fister, 2013, magistrsko delo
Opis: 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.
Ključne besede: swarm intelligence, evolutionary computation, bat algorithm, hybridization, review
Objavljeno: 06.09.2013; Ogledov: 2073; Prenosov: 210
Celotno besedilo (8,69 MB)
