Abstract
The hybrid multimodal optimization algorithm that combines a novel clustering method and fitness sharing method is presented in this paper. The only parameter required by the novel clustering method is the peak number. The clustering criteria include minimizing the square sum of the inner-group distance, maximizing the square sum of the inter-group distance, and the fitness value of the individuals. After each individual has been classified to the certain cluster, fitness sharing genetic algorithm is used to find multiple peaks simultaneously. The empirical study of the benchmark problems shows that the proposed method has satisfactory performance.
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Yu, X. (2005). A Novel Clustering Fitness Sharing Genetic Algorithm. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539117_146
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DOI: https://doi.org/10.1007/11539117_146
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28325-6
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