Filtros : "Swarm and Evolutionary Computation" Limpar

Filtros



Refine with date range


  • Source: Swarm and Evolutionary Computation. Unidade: EESC

    Subjects: INDÚSTRIA FARMACÊUTICA, CONTATOS COM CLIENTES, ALGORITMOS GENÉTICOS, ENGENHARIA DE PRODUÇÃO

    PrivadoAcesso à fonteDOIHow to cite
    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: 02 jun. 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 jun. 02 ] 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 jun. 02 ] Available from: https://doi.org/10.1016/j.swevo.2022.101149
  • Source: Swarm and Evolutionary Computation. Unidade: EESC

    Subjects: PROGRAMAÇÃO DA PRODUÇÃO, HEURÍSTICA, ENGENHARIA DE PRODUÇÃO

    PrivadoAcesso à fonteDOIHow to cite
    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: 02 jun. 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 jun. 02 ] 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 jun. 02 ] Available from: https://doi.org/10.1016/j.swevo.2020.100689
  • Source: Swarm and Evolutionary Computation. Unidade: EESC

    Subjects: ALGORITMOS GENÉTICOS, SIMULAÇÃO, TECNOLOGIA DA INFORMAÇÃO, MINERAÇÃO DE DADOS

    PrivadoAcesso à fonteDOIHow to cite
    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: 02 jun. 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 jun. 02 ] 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 jun. 02 ] Available from: https://doi.org/10.1016/j.swevo.2019.100618
  • Source: Swarm and Evolutionary Computation. Unidade: ICMC

    Subjects: COMPUTAÇÃO EVOLUTIVA, ALGORITMOS GENÉTICOS, PARETO OTIMALIDADE

    Acesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      MARTINS, Jean Paulo e DELBEM, Alexandre Cláudio Botazzo. Reproductive bias, linkage learning and diversity preservation in bi-objective evolutionary optimization. Swarm and Evolutionary Computation, v. 48, p. 145-155, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.swevo.2019.04.005. Acesso em: 02 jun. 2024.
    • APA

      Martins, J. P., & Delbem, A. C. B. (2019). Reproductive bias, linkage learning and diversity preservation in bi-objective evolutionary optimization. Swarm and Evolutionary Computation, 48, 145-155. doi:10.1016/j.swevo.2019.04.005
    • NLM

      Martins JP, Delbem ACB. Reproductive bias, linkage learning and diversity preservation in bi-objective evolutionary optimization [Internet]. Swarm and Evolutionary Computation. 2019 ; 48 145-155.[citado 2024 jun. 02 ] Available from: https://doi.org/10.1016/j.swevo.2019.04.005
    • Vancouver

      Martins JP, Delbem ACB. Reproductive bias, linkage learning and diversity preservation in bi-objective evolutionary optimization [Internet]. Swarm and Evolutionary Computation. 2019 ; 48 145-155.[citado 2024 jun. 02 ] Available from: https://doi.org/10.1016/j.swevo.2019.04.005
  • Source: Swarm and Evolutionary Computation. Unidade: EESC

    Subjects: SCHEDULING, ALGORITMOS DE SCHEDULING, HEURÍSTICA

    PrivadoAcesso à fonteDOIHow to cite
    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: 02 jun. 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 jun. 02 ] 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 jun. 02 ] Available from: https://doi.org/10.1016/j.swevo.2018.08.001
  • Source: Swarm and Evolutionary Computation. Unidade: EESC

    Subjects: ALGORITMOS GENÉTICOS, APRENDIZADO COMPUTACIONAL

    PrivadoAcesso à fonteDOIHow to cite
    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: 02 jun. 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 jun. 02 ] 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 jun. 02 ] Available from: https://doi.org/10.1016/j.swevo.2018.03.002
  • Source: Swarm and Evolutionary Computation. Unidade: ICMC

    Subjects: SISTEMAS EMBUTIDOS, COMPUTAÇÃO EVOLUTIVA, ROBÓTICA

    Acesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      MARTINS, Jean P. e DELBEM, Alexandre Cláudio Botazzo. Pairwise independence and its impact on estimation of distribution algorithms. Swarm and Evolutionary Computation, v. 27, p. 80-96, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.swevo.2015.10.001. Acesso em: 02 jun. 2024.
    • APA

      Martins, J. P., & Delbem, A. C. B. (2016). Pairwise independence and its impact on estimation of distribution algorithms. Swarm and Evolutionary Computation, 27, 80-96. doi:10.1016/j.swevo.2015.10.001
    • NLM

      Martins JP, Delbem ACB. Pairwise independence and its impact on estimation of distribution algorithms [Internet]. Swarm and Evolutionary Computation. 2016 ; 27 80-96.[citado 2024 jun. 02 ] Available from: https://doi.org/10.1016/j.swevo.2015.10.001
    • Vancouver

      Martins JP, Delbem ACB. Pairwise independence and its impact on estimation of distribution algorithms [Internet]. Swarm and Evolutionary Computation. 2016 ; 27 80-96.[citado 2024 jun. 02 ] Available from: https://doi.org/10.1016/j.swevo.2015.10.001
  • Source: Swarm and Evolutionary Computation. Unidade: ICMC

    Subjects: SISTEMAS EMBUTIDOS, COMPUTAÇÃO EVOLUTIVA, ROBÓTICA

    Acesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      LIMA, Telma Woerle de et al. Node-depth phylogenetic-based encoding, a spanning-tree representation for evolutionary algorithms: Part I: proposal and properties analysis. Swarm and Evolutionary Computation, v. 31, p. 1-10, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.swevo.2016.05.001. Acesso em: 02 jun. 2024.
    • APA

      Lima, T. W. de, Delbem, A. C. B., Soares, A. da S., Federson, F. M., London Junior, J. B. A., & Baalen, J. V. (2016). Node-depth phylogenetic-based encoding, a spanning-tree representation for evolutionary algorithms: Part I: proposal and properties analysis. Swarm and Evolutionary Computation, 31, 1-10. doi:10.1016/j.swevo.2016.05.001
    • NLM

      Lima TW de, Delbem ACB, Soares A da S, Federson FM, London Junior JBA, Baalen JV. Node-depth phylogenetic-based encoding, a spanning-tree representation for evolutionary algorithms: Part I: proposal and properties analysis [Internet]. Swarm and Evolutionary Computation. 2016 ; 31 1-10.[citado 2024 jun. 02 ] Available from: https://doi.org/10.1016/j.swevo.2016.05.001
    • Vancouver

      Lima TW de, Delbem ACB, Soares A da S, Federson FM, London Junior JBA, Baalen JV. Node-depth phylogenetic-based encoding, a spanning-tree representation for evolutionary algorithms: Part I: proposal and properties analysis [Internet]. Swarm and Evolutionary Computation. 2016 ; 31 1-10.[citado 2024 jun. 02 ] Available from: https://doi.org/10.1016/j.swevo.2016.05.001

Digital Library of Intellectual Production of Universidade de São Paulo     2012 - 2024