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Artigo de periodico
A novel BRKGA for the customer order scheduling with missing operations to minimize total tardiness (2022)
Abreu, Levi Ribeiro de; Prata, Bruno de Athayde; Gomes, Allan Costa; Santos, Stephanie Alencar Braga; Nagano, Marcelo Seido
Source: Swarm and Evolutionary Computation. Unidade: EESC
Subjects: INDÚSTRIA FARMACÊUTICA, CONTATOS COM CLIENTES, ALGORITMOS GENÉTICOS, ENGENHARIA DE PRODUÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ABREU, Levi Ribeiro de et al. A novel BRKGA for the customer order scheduling with missing operations to minimize total tardiness. Swarm and Evolutionary Computation, v. 75, p. 1-13, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.swevo.2022.101149. Acesso em: 17 out. 2024.
APA
Abreu, L. R. de, Prata, B. de A., Gomes, A. C., Santos, S. A. B., & Nagano, M. S. (2022). A novel BRKGA for the customer order scheduling with missing operations to minimize total tardiness. Swarm and Evolutionary Computation, 75, 1-13. doi:10.1016/j.swevo.2022.101149
NLM
Abreu LR de, Prata B de A, Gomes AC, Santos SAB, Nagano MS. A novel BRKGA for the customer order scheduling with missing operations to minimize total tardiness [Internet]. Swarm and Evolutionary Computation. 2022 ; 75 1-13.[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.swevo.2022.101149
Vancouver
Abreu LR de, Prata B de A, Gomes AC, Santos SAB, Nagano MS. A novel BRKGA for the customer order scheduling with missing operations to minimize total tardiness [Internet]. Swarm and Evolutionary Computation. 2022 ; 75 1-13.[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.swevo.2022.101149
Artigo de periodico
Heuristics and metaheuristics for the mixed no-idle flowshop with sequence-dependent setup times and total tardiness minimisation (2020)
Rossi, Fernando Luis; Nagano, Marcelo Seido
Source: Swarm and Evolutionary Computation. Unidade: EESC
Subjects: PROGRAMAÇÃO DA PRODUÇÃO, HEURÍSTICA, ENGENHARIA DE PRODUÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ROSSI, Fernando Luis e NAGANO, Marcelo Seido. Heuristics and metaheuristics for the mixed no-idle flowshop with sequence-dependent setup times and total tardiness minimisation. Swarm and Evolutionary Computation, v. 55, p. 1-19, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.swevo.2020.100689. Acesso em: 17 out. 2024.
APA
Rossi, F. L., & Nagano, M. S. (2020). Heuristics and metaheuristics for the mixed no-idle flowshop with sequence-dependent setup times and total tardiness minimisation. Swarm and Evolutionary Computation, 55, 1-19. doi:10.1016/j.swevo.2020.100689
NLM
Rossi FL, Nagano MS. Heuristics and metaheuristics for the mixed no-idle flowshop with sequence-dependent setup times and total tardiness minimisation [Internet]. Swarm and Evolutionary Computation. 2020 ; 55 1-19.[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.swevo.2020.100689
Vancouver
Rossi FL, Nagano MS. Heuristics and metaheuristics for the mixed no-idle flowshop with sequence-dependent setup times and total tardiness minimisation [Internet]. Swarm and Evolutionary Computation. 2020 ; 55 1-19.[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.swevo.2020.100689
Artigo de periodico
Unsupervised feature selection based on bio-inspired approaches (2020)
Martarelli, Nádia Junqueira; Nagano, Marcelo Seido
Source: Swarm and Evolutionary Computation. Unidade: EESC
Subjects: ALGORITMOS GENÉTICOS, SIMULAÇÃO, TECNOLOGIA DA INFORMAÇÃO, MINERAÇÃO DE DADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MARTARELLI, Nádia Junqueira e NAGANO, Marcelo Seido. Unsupervised feature selection based on bio-inspired approaches. Swarm and Evolutionary Computation, v. 52, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.swevo.2019.100618. Acesso em: 17 out. 2024.
APA
Martarelli, N. J., & Nagano, M. S. (2020). Unsupervised feature selection based on bio-inspired approaches. Swarm and Evolutionary Computation, 52. doi:10.1016/j.swevo.2019.100618
NLM
Martarelli NJ, Nagano MS. Unsupervised feature selection based on bio-inspired approaches [Internet]. Swarm and Evolutionary Computation. 2020 ; 52[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.swevo.2019.100618
Vancouver
Martarelli NJ, Nagano MS. Unsupervised feature selection based on bio-inspired approaches [Internet]. Swarm and Evolutionary Computation. 2020 ; 52[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.swevo.2019.100618
Artigo de periodico
An Iterated Greedy approach to integrate production by multiple parallel machines and distribution by a single capacitated vehicle (2019)
Tavares Neto, Roberto Fernandes; Nagano, Marcelo Seido
Source: Swarm and Evolutionary Computation. Unidade: EESC
Subjects: SCHEDULING, ALGORITMOS DE SCHEDULING, HEURÍSTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
TAVARES NETO, Roberto Fernandes e NAGANO, Marcelo Seido. An Iterated Greedy approach to integrate production by multiple parallel machines and distribution by a single capacitated vehicle. Swarm and Evolutionary Computation, v. 44, p. 612-621, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.swevo.2018.08.001. Acesso em: 17 out. 2024.
APA
Tavares Neto, R. F., & Nagano, M. S. (2019). An Iterated Greedy approach to integrate production by multiple parallel machines and distribution by a single capacitated vehicle. Swarm and Evolutionary Computation, 44, 612-621. doi:10.1016/j.swevo.2018.08.001
NLM
Tavares Neto RF, Nagano MS. An Iterated Greedy approach to integrate production by multiple parallel machines and distribution by a single capacitated vehicle [Internet]. Swarm and Evolutionary Computation. 2019 ; 44 612-621.[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.swevo.2018.08.001
Vancouver
Tavares Neto RF, Nagano MS. An Iterated Greedy approach to integrate production by multiple parallel machines and distribution by a single capacitated vehicle [Internet]. Swarm and Evolutionary Computation. 2019 ; 44 612-621.[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.swevo.2018.08.001
Artigo de periodico
A constructive evolutionary approach for feature selection in unsupervised learning (2018)
Martarelli, Nádia Junqueira; Nagano, Marcelo Seido
Source: Swarm and Evolutionary Computation. Unidade: EESC
Subjects: ALGORITMOS GENÉTICOS, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MARTARELLI, Nádia Junqueira e NAGANO, Marcelo Seido. A constructive evolutionary approach for feature selection in unsupervised learning. Swarm and Evolutionary Computation, v. 42, p. 125-137, 2018Tradução . . Disponível em: https://doi.org/10.1016/j.swevo.2018.03.002. Acesso em: 17 out. 2024.
APA
Martarelli, N. J., & Nagano, M. S. (2018). A constructive evolutionary approach for feature selection in unsupervised learning. Swarm and Evolutionary Computation, 42, 125-137. doi:10.1016/j.swevo.2018.03.002
NLM
Martarelli NJ, Nagano MS. A constructive evolutionary approach for feature selection in unsupervised learning [Internet]. Swarm and Evolutionary Computation. 2018 ; 42 125-137.[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.swevo.2018.03.002
Vancouver
Martarelli NJ, Nagano MS. A constructive evolutionary approach for feature selection in unsupervised learning [Internet]. Swarm and Evolutionary Computation. 2018 ; 42 125-137.[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.swevo.2018.03.002

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