A hybrid optimization method of harmony search and opposition-based learning

作者：Gao X Z^*; Wang X; Ovaska S J; Zenger K

来源：Engineering Optimization, 2012, 44(8): 895-914.

DOI：10.1080/0305215X.2011.628387

• harmony search (HS)
• opposition-based learning (OBL)
• hybrid optimization methods
• nonlinear function optimization
• optimal wind generator design

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 optimum in an efficient way. In this article, a hybrid optimization approach is proposed and studied, in which the HS is merged together with the opposition-based learning (OBL). The modified HS, namely HS-OBL, has an improved convergence property. Optimization of 24 typical benchmark functions and an optimal wind generator design case study demonstrate that the HS-OBL can indeed yield a superior optimization performance over the regular HS method.

• 出版日期2012