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Evolutionary algorithms with clustering for dynamic fitness landscapes

Aragón, Victoria S. et al · SEDICI UNLP · 2005

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Author / responsible party
Aragón, Victoria S. et al
Publisher
SEDICI UNLP
Year
2005
Language
English

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Interest on dynamic multimodal functions risen over the last years since many real problems have this feature. On these problems, the goal is no longer to find the global optimal, but to track their progression through the space as closely as possible. This paper presents three evolutionary algorithms for dynamic fitness landscapes. In order to maintain diversity in the population they use two clustering techniques and a macromutation operator. Besides, this paper compares two crossover operators: arithmetic and multiparents two points, respectively. Effectiveness and limitations of each algorithm are discuss anda analyzed. Facultad de Informática

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APA 7

Aragón, V. S. E. A. (2005). Evolutionary algorithms with clustering for dynamic fitness landscapes. http://sedici.unlp.edu.ar/handle/10915/9593

MLA

Aragón, Victoria S. et al. "Evolutionary algorithms with clustering for dynamic fitness landscapes." 2005. http://sedici.unlp.edu.ar/handle/10915/9593.

Chicago

Aragón, Victoria S. et al. 2005. "Evolutionary algorithms with clustering for dynamic fitness landscapes.". http://sedici.unlp.edu.ar/handle/10915/9593.

Harvard

Aragón, V. S. E. A. 2005, Evolutionary algorithms with clustering for dynamic fitness landscapes, SEDICI UNLP, available at: http://sedici.unlp.edu.ar/handle/10915/9593 [Accessed 8 Aug. 2026].

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Title
Evolutionary algorithms with clustering for dynamic fitness landscapes
Author / contributors
Aragón, Victoria S. et al
Publisher
SEDICI UNLP
Publication year
2005
Language
English

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Ciencias Informáticas; Algorithms; Information Systems
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