A hybrid PBIL-based Harmony Search method with application in wind generator optimization

The Harmony Search (HS) method is a popular meta-heuristic optimization algorithm, which has been extensively employed to handle various engineering problems. However, it sometimes fails to offer a satisfactory convergence performance. In this paper, we propose and study a hybrid HS approach, HS-PBIL, by merging the HS together with the Population-Based Incremental Learning (PBIL). Numerical simulations demonstrate that our HS-PBIL is well capable of outperforming the regular HS method in attacking a practical wind generator optimization problem.