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Trabalho de evento-resumo
Handling crossover bias to improve diversity in multiobjective evolutionary optimization (2015)
Martins, Jean; Delbem, Alexandre Cláudio Botazzo
Source: Proceedings. Conference titles: Genetic and Evolutionary Computation Conference - GECCO'15. Unidade: ICMC
Subjects: SISTEMAS EMBUTIDOS, COMPUTAÇÃO EVOLUTIVA, ROBÓTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MARTINS, Jean e DELBEM, Alexandre Cláudio Botazzo. Handling crossover bias to improve diversity in multiobjective evolutionary optimization. 2015, Anais.. New York, NY: ACM, 2015. Disponível em: https://doi.org/10.1145/2739482.2764703. Acesso em: 10 nov. 2024.
APA
Martins, J., & Delbem, A. C. B. (2015). Handling crossover bias to improve diversity in multiobjective evolutionary optimization. In Proceedings. New York, NY: ACM. doi:10.1145/2739482.2764703
NLM
Martins J, Delbem ACB. Handling crossover bias to improve diversity in multiobjective evolutionary optimization [Internet]. Proceedings. 2015 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1145/2739482.2764703
Vancouver
Martins J, Delbem ACB. Handling crossover bias to improve diversity in multiobjective evolutionary optimization [Internet]. Proceedings. 2015 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1145/2739482.2764703
Trabalho de evento-resumo
On the effectiveness of genetic algorithms for the multidimensional knapsack problem (2014)
Martins, Jean; Longo, Humberto; Delbem, Alexandre Cláudio Botazzo
Source: Proceedings. Conference titles: International Conference on Genetic and Evolutionary Computation - GECCO'14. Unidade: ICMC
Subjects: SISTEMAS EMBUTIDOS, COMPUTAÇÃO EVOLUTIVA, ROBÓTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MARTINS, Jean e LONGO, Humberto e DELBEM, Alexandre Cláudio Botazzo. On the effectiveness of genetic algorithms for the multidimensional knapsack problem. 2014, Anais.. New York, NY: ACM, 2014. Disponível em: https://doi.org/10.1145/2598394.2598477. Acesso em: 10 nov. 2024.
APA
Martins, J., Longo, H., & Delbem, A. C. B. (2014). On the effectiveness of genetic algorithms for the multidimensional knapsack problem. In Proceedings. New York, NY: ACM. doi:10.1145/2598394.2598477
NLM
Martins J, Longo H, Delbem ACB. On the effectiveness of genetic algorithms for the multidimensional knapsack problem [Internet]. Proceedings. 2014 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1145/2598394.2598477
Vancouver
Martins J, Longo H, Delbem ACB. On the effectiveness of genetic algorithms for the multidimensional knapsack problem [Internet]. Proceedings. 2014 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1145/2598394.2598477
Trabalho de evento
Multimodality and the linkage-learning difficulty of additively separable functions (2014)
Martins, Jean; Delbem, Alexandre Cláudio Botazzo
Source: Proceedings. Conference titles: International Conference on Genetic and Evolutionary Computation - GECCO'14. Unidade: ICMC
Subjects: SISTEMAS EMBUTIDOS, COMPUTAÇÃO EVOLUTIVA, ROBÓTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MARTINS, Jean e DELBEM, Alexandre Cláudio Botazzo. Multimodality and the linkage-learning difficulty of additively separable functions. 2014, Anais.. New York, NY: ACM, 2014. Disponível em: https://doi.org/10.1145/2576768.2598281. Acesso em: 10 nov. 2024.
APA
Martins, J., & Delbem, A. C. B. (2014). Multimodality and the linkage-learning difficulty of additively separable functions. In Proceedings. New York, NY: ACM. doi:10.1145/2576768.2598281
NLM
Martins J, Delbem ACB. Multimodality and the linkage-learning difficulty of additively separable functions [Internet]. Proceedings. 2014 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1145/2576768.2598281
Vancouver
Martins J, Delbem ACB. Multimodality and the linkage-learning difficulty of additively separable functions [Internet]. Proceedings. 2014 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1145/2576768.2598281

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