Chaos optimization algorithm (COA) as a novel method of global optimization has attracted much attention. In order to address the COA's deficiencies in dealing with the large space and high-dimension optimization problems, a bi-directional chaos optimization algorithm (BCOA) is proposed. The main idea of BCOA is to adjust the approach of second carrier wave and to realize the bi-directional search in the sub-optimal solutions rather than the unidirectional search. Moreover, the parameter of second carrier wave is analyzed. The experiments on benchmark functions show that BCOA is capable of improving the search performance significantly no matter in convergent speed or precision. It is considerably better and more efficient to tackle the large space and high-dimension multimodal optimization problems.
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