A New Harmony Search method in 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 does not store or utilize the useful knowledge gained during its search procedure in an efficient way. In this paper, we propose and study a new optimization approach, in which the HS method is merged together with the Cultural Algorithm (CA). Our modified HS method, namely HS-CA, has the feature of embedded problem-solving knowledge. The HS-CA is further employed in an optimal wind generator design problem, and it can yield a superior optimization performance over the original HS method.

[1]  Riccardo Poli,et al.  Foundations of Genetic Programming , 1999, Springer Berlin Heidelberg.

[2]  Zong Woo Geem,et al.  Harmony Search Optimization: Application to Pipe Network Design , 2002 .

[3]  Robert G. Reynolds,et al.  Cultural algorithms: modeling of how cultures learn to solve problems , 2004, 16th IEEE International Conference on Tools with Artificial Intelligence.

[4]  Robert G. Reynolds,et al.  Knowledge-based self-adaptation in evolutionary programming using cultural algorithms , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[5]  David H. Wolpert,et al.  No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..

[6]  Zong Woo Geem,et al.  A New Heuristic Optimization Algorithm: Harmony Search , 2001, Simul..

[7]  Valéria Hrabovcová,et al.  Design of Rotating Electrical Machines , 2009 .

[8]  Xiao Zhi Gao,et al.  Fusion of clonal selection algorithm and harmony search method in optimisation of fuzzy classification systems , 2009, Int. J. Bio Inspired Comput..

[9]  K. Lee,et al.  A new structural optimization method based on the harmony search algorithm , 2004 .

[10]  D. E. Goldberg,et al.  Genetic Algorithms in Search , 1989 .

[11]  Xiaolei Wang,et al.  UNI-MODAL AND MULTI-MODAL OPTIMIZATION USING MODIFIED HARMONY SEARCH METHODS , 2009 .

[12]  Andries Petrus Engelbrecht,et al.  Fundamentals of Computational Swarm Intelligence , 2005 .

[13]  Robert G. Reynolds,et al.  CAEP: An Evolution-Based Tool for Real-Valued Function Optimization Using Cultural Algorithms , 1998, Int. J. Artif. Intell. Tools.

[14]  K. Lee,et al.  A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice , 2005 .