A novel Harmony Search method with dual memory

Author

Gao, X.Z. ; Wang, X. ; Zenger, K. ; Wang, Xiaofeng

Author_Institution

Coll. of Inf. Eng., Shanghai Maritime Univ., Shanghai, China

fYear

2012

fDate

14-17 Oct. 2012

Firstpage

177

Lastpage

183

Abstract

The Harmony Search (HS) method is an emerging meta-heuristic optimization algorithm, which has been widely employed to deal with various optimization problems during the past decade. However, like most of the evolutionary computation techniques, it sometimes suffers from a rather slow search speed, and even fails to find the global optima in an efficient way. In this paper, a new HS method with dual memory, namely DUAL-HS, is proposed and studied. The secondary memory in the DUAL-HS takes advantage of the Opposition-Based Learning (OBL) to evolve so that the quality of all the harmony memory members can be significantly improved. Optimization of 25 typical benchmark functions demonstrate that compared with the regular HS method, our DUAL-HS has an enhanced convergence property.

Keywords

evolutionary computation; learning (artificial intelligence); optimisation; search problems; DUAL-HS; HS method; OBL; convergence property; dual harmony memory; evolutionary computation techniques; global optima; harmony memory; harmony search method; meta-heuristic optimization algorithm; opposition-based learning; secondary memory; slow search speed; Algorithm design and analysis; Convergence; Educational institutions; Genetic algorithms; Linear programming; Optimization; Search problems; Harmony Search (HS); Opposition-Based Learning (OBL); dual harmony memory; hybrid optimization methods; nonlinear function optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on

Conference_Location

Seoul

Print_ISBN

978-1-4673-1713-9

Electronic_ISBN

978-1-4673-1712-2

Type

conf

DOI

10.1109/ICSMC.2012.6377696

Filename

6377696