Ensemble of niching algorithms

Although niching algorithms have been investigated for almost four decades as effective procedures to obtain several good and diverse solutions of an optimization problem, no effort has been reported on combining different niching algorithms to form an effective ensemble of niching algorithms. In this paper, we propose an ensemble of niching algorithms (ENA) and illustrate the concept by an instantiation which is realized using four different parallel populations. The offspring of each population is considered by all parallel populations. The instantiation is tested on a set of 16 real and binary problems and compared against the single niching methods with respect to searching ability and computation time. Results confirm that ENA method is as good as or better than the best single method in it on every test problem. Moreover, comparison with other state-of-the-art niching algorithms demonstrates the competitiveness of our proposed ENA.

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