Chaos-differential Evolution for Multiple Sequence Alignment

Author

Hu, Gui-wu

Author_Institution

Sch. of Math. & Comput. Sci., Guangdong Univ. of Bus. Studies, Guangzhou, China

Volume

2

fYear

2009

fDate

21-22 Nov. 2009

Firstpage

556

Lastpage

558

Abstract

Multiple sequence alignment is one of the most important and challenging problem in bioinformatics, which is known as NP-hard problem. In this paper, a chaos-differential evolution (CDE) is proposed to solve MSA. In the proposed CDE algorithm, DE and chaos are hybridized to combine the evolutionary searching ability of DE and overcoming local optima of chaotic local search. Simulation shows that novel algorithm has superior performance compared to other existing algorithms.

Keywords

bioinformatics; chaos; computational complexity; evolutionary computation; search problems; NP-hard problem; bioinformatics; chaos-differential evolution; chaotic local search; evolutionary searching ability; multiple sequence alignment; Bioinformatics; Chaos; Computational intelligence; Evolution (biology); Information technology; Mathematics; NP-hard problem; Optimization methods; Particle swarm optimization; Sequences; Multiple Sequence Alignment; chaos; differential evolution; local optima;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on

Conference_Location

Nanchang

Print_ISBN

978-0-7695-3859-4

Type

conf

DOI

10.1109/IITA.2009.511

Filename

5369566