A Parameter-less Evolution Strategy for Global Optimization
نویسنده
چکیده
Several evolutionary approaches have been applied to global optimization problems with significant success. Evolution strategies proved to be efficient global optimizers. However, these algorithms have several parameters which the setting is not simple. Thus, it is crucial to investigate how to set dynamically these parameters during the search. In this paper, a new parameter-less evolution strategy, which has only one single parameter to set, is proposed. This algorithm is compared with the traditional evolution strategies considering a set of difficult test problems. The results obtained indicate a promising performance of the new approach.
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