Solving equations by hybrid evolutionary computation techniques

Author

He, Jun ; Xu, Jiyou ; Yao, Xin

Author_Institution

Dept. of Comput. Sci., Northerm Jiaotong Univ., Beijing, China

Volume

4

Issue

3

fYear

2000

fDate

9/1/2000 12:00:00 AM

Firstpage

295

Lastpage

304

Abstract

Evolutionary computation techniques have mostly been used to solve various optimization and learning problems. This paper describes a novel application of evolutionary computation techniques to equation solving. Several combinations of evolutionary computation techniques and classical numerical methods are proposed to solve linear and partial differential equations. The hybrid algorithms have been compared with the well-known classical numerical methods. The experimental results show that the proposed hybrid algorithms outperform the classical numerical methods significantly in terms of effectiveness and efficiency

Keywords

evolutionary computation; linear differential equations; numerical analysis; partial differential equations; equation solving; hybrid evolutionary computation techniques; learning; linear differential equations; numerical methods; optimization; partial differential equations; Computational modeling; Computer science; Convergence of numerical methods; Differential equations; Evolutionary computation; Genetic mutations; Helium; Linear systems; Partial differential equations; Testing;

fLanguage

English

Journal_Title

Evolutionary Computation, IEEE Transactions on

Publisher

ieee

ISSN

1089-778X

Type

jour

DOI

10.1109/4235.873239

Filename

873239