Title :
A novel algorithm for multimodal function optimization based on evolution strategy
Author :
Im, Chang-Hwan ; Kim, Hong-Kyu ; Jung, Hyun-Kyo ; Choi, Kyung
Author_Institution :
Sch. of Electr. Eng., Seoul Nat. Univ., South Korea
fDate :
3/1/2004 12:00:00 AM
Abstract :
In this paper, a novel algorithm for multimodal function optimization is proposed, based on the concept of evolution strategy. A new concept, named restricted evolution, shows more improved characteristics than conventional approaches that have been used for multimodal function optimization. The efficiency and usefulness of the proposed method will be verified by the application to various cases including practical optimization problems.
Keywords :
evolutionary computation; function approximation; evolution strategy; multimodal function optimization; optimization problems; restricted evolution; Algorithm design and analysis; Clustering algorithms; Convergence; Genetic algorithms; Heuristic algorithms; Optimization methods; Shape; Simulated annealing;
Journal_Title :
Magnetics, IEEE Transactions on
DOI :
10.1109/TMAG.2004.824805
