Iterated local search with Powell's method: a memetic algorithm for continuous global optimization

In combinatorial solution spaces Iterated Local Search (ILS) turns out to be exceptionally successful. The question arises: is ILS also capable of improving the optimization process in continuous solution spaces? To demonstrate that hybridization leads to powerful techniques in continuous domains, we introduce a hybrid meta-heuristic that integrates Powell's direct search method. It combines direct search with elements from population based evolutionary optimization. The approach is analyzed experimentally on a set of well known test problems and compared to a stateof-the-art technique, i.e., a restart variant of the Covariance Matrix Adaptation Evolution Strategy with increasing population sizes (G-CMA-ES). It turns out that the populationbased Powell-ILS is competitive to the CMA-ES, in some cases even significantly faster and behaves more robust than the pure strategy of Powell in multimodal fitness landscapes. Further experiments on the perturbation mechanism, population sizes...

• Type: Journal
• Year: 2010
• Where: MEMETIC
• Authors: Oliver Kramer
• Keywords: Direct Search, Direct Search Method, Forensic Engineering, Local Search, MEMETIC 2010