A modified harmony search method for wind generator design. (1st January 2013)

• Record Type: Journal Article
• Authors: Gao, Xiao-Zhi; Wang, Xiaolei; Zenger, Kai
• Is Part Of: International journal of bio-inspired computation. Volume 5:Number 6(2013)
• Page Start: 336
• Page End: 349
• Publication Date: 2013-01-01
• Subjects: harmony search -- HS -- opposition-based learning -- OBL -- dual harmony memory -- hybrid optimisation methods -- non-linear function optimisation -- wind generator design; Biologically-inspired computing -- Periodicals; Computational biology -- Periodicals; 572.0285
• Languages: English
• ISSNs: 1758-0366

Abstract

The harmony search (HS) method is an emerging meta-heuristic optimisation algorithm, which has been widely employed to deal with various optimisation 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. Optimisation of 25 typical benchmark functions demonstrate that compared with the regular HS method, our DUAL-HS has an enhanced convergence property. The DUAL-HS is further applied for the wind generator design, in which it has also shown a satisfactory optimisation performance.