ǂA ǂnovel hybrid self-adaptive bat algorithm

Iztok Fister (Author), Simon Fong (Author), Janez Brest (Author), Iztok Fister (Author)

Abstract

Nature-inspired algorithms attract many researchers worldwide for solving the hardest optimization problems. One of the newest members of this extensive family is the bat algorithm. To date,many variants of this algorithm have emerged for solving continuous as well as combinatorial problems. One of the more promising variants, a self-adaptive bat algorithm, has recently been proposed that enables a self-adaptation of its control parameters. In this paper, we have hybridized this algorithmusing differentDE strategies and applied these as a local search heuristics for improving the current best solution directing the swarm of a solution towards the better regions within a search space.The results of exhaustive experiments were promising and have encouraged us to invest more efforts into developing in this direction.

Keywords

algorithms;optimization;

Data

Language:	English
Year of publishing:	2014
Typology:	1.01 - Original Scientific Article
Organization:	UM FERI - Faculty of Electrical Engineering and Computer Science
UDC:	004.4
COBISS:	17789206
ISSN:	1537-744X
Views:	1374
Downloads:	316
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	Slovenian
Secondary keywords:	algoritmi;optimizacija;
URN:	URN:SI:UM:
Type (COBISS):	Scientific work
Pages:	str. 1-12
Issue:	ǂID ǂ709738
Chronology:	2014
DOI:	10.1155/2014/709738
ID:	10842812