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Cellular memetic algorithms

Alba Torres, Enrique et al · SEDICI UNLP · 2005

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This work is focussed on the development and analysis of a new class of algorithms, called cellular memetic algorithms (cMAs), which will be evaluated here on the satisfiability problem (SAT). For describing a cMA, we study the effects of adding specific knowledge of the problem to the fitness function, the crossover and mutation operators, and to the local search step in a canonical cellular genetic algorithm (cGA). Hence, the proposed cMAs are the result of including these hybridization techniques in different structural ways into a canonical cGA. We conclude that the performance of the cGA is largely improved by these hybrid extensions. The accuracy and efficiency of the resulting cMAs are even better than those of the best existing heuristics for SAT in many cases. Facultad de Informática

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APA 7

Alba Torres, E. E. A. (2005). Cellular memetic algorithms. http://sedici.unlp.edu.ar/handle/10915/9602

MLA

Alba Torres, Enrique et al. "Cellular memetic algorithms." 2005. http://sedici.unlp.edu.ar/handle/10915/9602.

Chicago

Alba Torres, Enrique et al. 2005. "Cellular memetic algorithms.". http://sedici.unlp.edu.ar/handle/10915/9602.

Harvard

Alba Torres, E. E. A. 2005, Cellular memetic algorithms, SEDICI UNLP, available at: http://sedici.unlp.edu.ar/handle/10915/9602 [Accessed 8 Aug. 2026].

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Title
Cellular memetic algorithms
Author / contributors
Alba Torres, Enrique et al
Publisher
SEDICI UNLP
Publication year
2005
Language
English

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