A Hybrid Harmony Search Method Based on OBL

Author

Gao, X.Z. ; Wang, X. ; Ovaska, S.J.

Author_Institution

Dept. of Electr. Eng., Aalto Univ., Espoo, Finland

fYear

2010

fDate

11-13 Dec. 2010

Firstpage

140

Lastpage

145

Abstract

The Harmony Search (HS) method is an emerging meta-heuristic optimization algorithm. However, like most of the evolutionary computation techniques, it sometimes suffers from a rather slow search speed, and fails to find the global optima in an efficient way. In this paper, we propose and study a hybrid optimization approach, in which the HS is merged together with the Opposition-Based Learning (OBL). Our modified HS, namely HS-OBL, has an improved convergence property. Simulations of 23 typical benchmark problems demonstrate that the HS-OBL can indeed yield a superior optimization performance over the regular HS method.

Keywords

convergence; evolutionary computation; search problems; HS-OBL; convergence property; evolutionary computation; global optima; hybrid harmony search; hybrid optimization; metaheuristic optimization; opposition-based learning; regular HS method; superior optimization performance; Computational modeling; Convergence; Ellipsoids; Gallium; Genetic algorithms; Optimization methods; Harmony Search (HS); Opposition-Based Learning (OBL); hybrid optimization methods; nonlinear function optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Science and Engineering (CSE), 2010 IEEE 13th International Conference on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-9591-7

Electronic_ISBN

978-0-7695-4323-9

Type

conf

DOI

10.1109/CSE.2010.26

Filename

5692468