A hybrid optimization method for wind generator design

The Harmony Search (HS) method is an emerging meta-heuristic optimization algorithm. However, like most of the evolutionary computation techniques, the HS does not store or utilize the useful knowledge gained during the search procedure in an efficient way. In this paper, we propose and study a hybrid optimization approach, in which the HS is merged together with the Cultural Algorithm (CA). Our modified HS method, namely HS-CA, has the interesting feature of embedded problem-solving knowledge. Simulations of some typical benchmark problems demonstrate that the HS-CA can yield a superior optimization performance over the regular HS algorithm. We also apply the proposed HS-CA in a case study of the optimal wind generator design to further examine its effectiveness.