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  • Source: IEEE Transactions on Visualization and Computer Graphics. Unidade: ICMC

    Subjects: COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS, INTELIGÊNCIA ARTIFICIAL

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      ETEMADPOUR, Ronak et al. Perception-based evaluation of projection methods for multidimensional data visualization. IEEE Transactions on Visualization and Computer Graphics, v. 21, n. ja 2015, p. 81-94, 2015Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2014.2330617. Acesso em: 10 jun. 2024.
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      Etemadpour, R., Motta, R., Paiva, J. G. de S., Minghim, R., Oliveira, M. C. F. de, & Linsen, L. (2015). Perception-based evaluation of projection methods for multidimensional data visualization. IEEE Transactions on Visualization and Computer Graphics, 21( ja 2015), 81-94. doi:10.1109/TVCG.2014.2330617
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      Etemadpour R, Motta R, Paiva JG de S, Minghim R, Oliveira MCF de, Linsen L. Perception-based evaluation of projection methods for multidimensional data visualization [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2015 ; 21( ja 2015): 81-94.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1109/TVCG.2014.2330617
    • Vancouver

      Etemadpour R, Motta R, Paiva JG de S, Minghim R, Oliveira MCF de, Linsen L. Perception-based evaluation of projection methods for multidimensional data visualization [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2015 ; 21( ja 2015): 81-94.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1109/TVCG.2014.2330617
  • Source: IEEE Transactions on Visualization and Computer Graphics. Unidade: ICMC

    Subjects: COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS, INTELIGÊNCIA ARTIFICIAL

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      PAIVA, José Gustavo S et al. An approach to supporting incremental visual data classification. IEEE Transactions on Visualization and Computer Graphics, v. 21, n. ja 2015, p. 4-17, 2015Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2014.2331979. Acesso em: 10 jun. 2024.
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      Paiva, J. G. S., Schwartz, W. R., Pedrini, H., & Minghim, R. (2015). An approach to supporting incremental visual data classification. IEEE Transactions on Visualization and Computer Graphics, 21( ja 2015), 4-17. doi:10.1109/TVCG.2014.2331979
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      Paiva JGS, Schwartz WR, Pedrini H, Minghim R. An approach to supporting incremental visual data classification [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2015 ; 21( ja 2015): 4-17.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1109/TVCG.2014.2331979
    • Vancouver

      Paiva JGS, Schwartz WR, Pedrini H, Minghim R. An approach to supporting incremental visual data classification [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2015 ; 21( ja 2015): 4-17.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1109/TVCG.2014.2331979
  • Source: IEEE Transactions on Visualization and Computer Graphics. Unidade: ICMC

    Subjects: COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS, GEOMETRIA COMPUTACIONAL, OTIMIZAÇÃO COMBINATÓRIA

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      GOMEZ-NIETO, Erick et al. Similarity preserving snippet-based visualization of web search results. IEEE Transactions on Visualization and Computer Graphics, v. 20, n. 3, p. 457-470, 2014Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2013.242. Acesso em: 10 jun. 2024.
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      Gomez-Nieto, E., Roman, F. S., Pagliosa, P., Casaca, W., Helou, E. S., Oliveira, M. C. F. de, & Nonato, L. G. (2014). Similarity preserving snippet-based visualization of web search results. IEEE Transactions on Visualization and Computer Graphics, 20( 3), 457-470. doi:10.1109/TVCG.2013.242
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      Gomez-Nieto E, Roman FS, Pagliosa P, Casaca W, Helou ES, Oliveira MCF de, Nonato LG. Similarity preserving snippet-based visualization of web search results [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2014 ; 20( 3): 457-470.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1109/TVCG.2013.242
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      Gomez-Nieto E, Roman FS, Pagliosa P, Casaca W, Helou ES, Oliveira MCF de, Nonato LG. Similarity preserving snippet-based visualization of web search results [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2014 ; 20( 3): 457-470.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1109/TVCG.2013.242
  • Source: Neurocomputing. Conference titles: Brazilian Symposium on Neural Networks - SBRN. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, OTIMIZAÇÃO COMBINATÓRIA

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      LIANG, Xiaoming e LIANG, Zhao. Effect of nonidentical signal phases on signal amplification of two coupled excitable neurons. Neurocomputing. Amsterdam: Elsevier. Disponível em: https://doi.org/10.1016/j.neucom.2013.06.041. Acesso em: 10 jun. 2024. , 2014
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      Liang, X., & Liang, Z. (2014). Effect of nonidentical signal phases on signal amplification of two coupled excitable neurons. Neurocomputing. Amsterdam: Elsevier. doi:10.1016/j.neucom.2013.06.041
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      Liang X, Liang Z. Effect of nonidentical signal phases on signal amplification of two coupled excitable neurons [Internet]. Neurocomputing. 2014 ; 127 21-29.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.neucom.2013.06.041
    • Vancouver

      Liang X, Liang Z. Effect of nonidentical signal phases on signal amplification of two coupled excitable neurons [Internet]. Neurocomputing. 2014 ; 127 21-29.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.neucom.2013.06.041
  • Source: Neurocomputing. Conference titles: Brazilian Symposium on Neural Networks - SBRN. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, OTIMIZAÇÃO COMBINATÓRIA

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      CUPERTINO, Thiago H e GUELERI, Roberto e LIANG, Zhao. A semi-supervised classification technique based on interacting forces. Neurocomputing. Amsterdam: Elsevier. Disponível em: https://doi.org/10.1016/j.neucom.2013.05.050. Acesso em: 10 jun. 2024. , 2014
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      Cupertino, T. H., Gueleri, R., & Liang, Z. (2014). A semi-supervised classification technique based on interacting forces. Neurocomputing. Amsterdam: Elsevier. doi:10.1016/j.neucom.2013.05.050
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      Cupertino TH, Gueleri R, Liang Z. A semi-supervised classification technique based on interacting forces [Internet]. Neurocomputing. 2014 ; 127 43-51.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.neucom.2013.05.050
    • Vancouver

      Cupertino TH, Gueleri R, Liang Z. A semi-supervised classification technique based on interacting forces [Internet]. Neurocomputing. 2014 ; 127 43-51.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.neucom.2013.05.050
  • Source: Neurocomputing. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, OTIMIZAÇÃO COMBINATÓRIA

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      CUPERTINO, Thiago H e HUERTAS, Jean e LIANG, Zhao. Data clustering using controlled consensus in complex networks. Neurocomputing, v. 118, p. 132-140, 2013Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2013.02.026. Acesso em: 10 jun. 2024.
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      Cupertino, T. H., Huertas, J., & Liang, Z. (2013). Data clustering using controlled consensus in complex networks. Neurocomputing, 118, 132-140. doi:10.1016/j.neucom.2013.02.026
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      Cupertino TH, Huertas J, Liang Z. Data clustering using controlled consensus in complex networks [Internet]. Neurocomputing. 2013 ; 118 132-140.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.neucom.2013.02.026
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      Cupertino TH, Huertas J, Liang Z. Data clustering using controlled consensus in complex networks [Internet]. Neurocomputing. 2013 ; 118 132-140.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.neucom.2013.02.026
  • Source: Neurocomputing. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, OTIMIZAÇÃO COMBINATÓRIA

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      SILVA, Thiago C e LIANG, Zhao. Semi-supervised learning guided by the modularity measure in complex networks. Neurocomputing, v. fe 2012, n. 1, p. 30-37, 2012Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2011.04.042. Acesso em: 10 jun. 2024.
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      Silva, T. C., & Liang, Z. (2012). Semi-supervised learning guided by the modularity measure in complex networks. Neurocomputing, fe 2012( 1), 30-37. doi:10.1016/j.neucom.2011.04.042
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      Silva TC, Liang Z. Semi-supervised learning guided by the modularity measure in complex networks [Internet]. Neurocomputing. 2012 ; fe 2012( 1): 30-37.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.neucom.2011.04.042
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      Silva TC, Liang Z. Semi-supervised learning guided by the modularity measure in complex networks [Internet]. Neurocomputing. 2012 ; fe 2012( 1): 30-37.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.neucom.2011.04.042
  • Source: IEEE Transactions on Visualization and Computers Graphics. Unidade: ICMC

    Subjects: COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS, GEOMETRIA COMPUTACIONAL, MECÂNICA DOS FLUÍDOS COMPUTACIONAL

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      JOIA, Paulo et al. Local affine multidimensional projection. IEEE Transactions on Visualization and Computers Graphics, v. 17, n. 12, p. 2563-2571, 2011Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2011.220. Acesso em: 10 jun. 2024.
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      Joia, P., Paulovich, F. V., Coimbra, D., Cuminato, J. A., & Nonato, L. G. (2011). Local affine multidimensional projection. IEEE Transactions on Visualization and Computers Graphics, 17( 12), 2563-2571. doi:10.1109/TVCG.2011.220
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      Joia P, Paulovich FV, Coimbra D, Cuminato JA, Nonato LG. Local affine multidimensional projection [Internet]. IEEE Transactions on Visualization and Computers Graphics. 2011 ; 17( 12): 2563-2571.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1109/TVCG.2011.220
    • Vancouver

      Joia P, Paulovich FV, Coimbra D, Cuminato JA, Nonato LG. Local affine multidimensional projection [Internet]. IEEE Transactions on Visualization and Computers Graphics. 2011 ; 17( 12): 2563-2571.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1109/TVCG.2011.220
  • Source: IEEE Transactions on Visualization and Computer Graphics. Unidade: ICMC

    Subjects: COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS

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      PAIVA, José Gustavo S et al. Improved similarity trees and their application to visual data classification. IEEE Transactions on Visualization and Computer Graphics, v. 17, n. 12, p. 2459-2468, 2011Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2011.212. Acesso em: 10 jun. 2024.
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      Paiva, J. G. S., Florian-Cruz, L., Pedrini, H., Telles, G. P., & Minghim, R. (2011). Improved similarity trees and their application to visual data classification. IEEE Transactions on Visualization and Computer Graphics, 17( 12), 2459-2468. doi:10.1109/TVCG.2011.212
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      Paiva JGS, Florian-Cruz L, Pedrini H, Telles GP, Minghim R. Improved similarity trees and their application to visual data classification [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2011 ; 17( 12): 2459-2468.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1109/TVCG.2011.212
    • Vancouver

      Paiva JGS, Florian-Cruz L, Pedrini H, Telles GP, Minghim R. Improved similarity trees and their application to visual data classification [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2011 ; 17( 12): 2459-2468.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1109/TVCG.2011.212
  • Source: IEEE Transactions on Visualization and Computer Graphics. Unidade: ICMC

    Subjects: COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS

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      ERSOY, Ozan et al. Skeleton-based edge bundling for graph visualization. IEEE Transactions on Visualization and Computer Graphics, v. 17, n. 12, p. 2364-2373, 2011Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2011.233. Acesso em: 10 jun. 2024.
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      Ersoy, O., Hurter, C., Paulovich, F. V., Cantareira, G., & Telea, A. (2011). Skeleton-based edge bundling for graph visualization. IEEE Transactions on Visualization and Computer Graphics, 17( 12), 2364-2373. doi:10.1109/TVCG.2011.233
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      Ersoy O, Hurter C, Paulovich FV, Cantareira G, Telea A. Skeleton-based edge bundling for graph visualization [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2011 ; 17( 12): 2364-2373.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1109/TVCG.2011.233
    • Vancouver

      Ersoy O, Hurter C, Paulovich FV, Cantareira G, Telea A. Skeleton-based edge bundling for graph visualization [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2011 ; 17( 12): 2364-2373.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1109/TVCG.2011.233
  • Source: IEEE Transactions on Visualization and Computers Graphics. Unidade: ICMC

    Subjects: COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS, GEOMETRIA COMPUTACIONAL

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      PAULOVICH, Fernando Vieira e SILVA, Claudio T. e NONATO, Luis Gustavo. Two-phase mapping for projecting massive data sets. IEEE Transactions on Visualization and Computers Graphics, v. 16, n. 6, p. 1281-1290, 2010Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2010.270. Acesso em: 10 jun. 2024.
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      Paulovich, F. V., Silva, C. T., & Nonato, L. G. (2010). Two-phase mapping for projecting massive data sets. IEEE Transactions on Visualization and Computers Graphics, 16( 6), 1281-1290. doi:10.1109/TVCG.2010.270
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      Paulovich FV, Silva CT, Nonato LG. Two-phase mapping for projecting massive data sets [Internet]. IEEE Transactions on Visualization and Computers Graphics. 2010 ; 16( 6): 1281-1290.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1109/TVCG.2010.270
    • Vancouver

      Paulovich FV, Silva CT, Nonato LG. Two-phase mapping for projecting massive data sets [Internet]. IEEE Transactions on Visualization and Computers Graphics. 2010 ; 16( 6): 1281-1290.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1109/TVCG.2010.270
  • Source: Neurocomputing. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, OTIMIZAÇÃO COMBINATÓRIA

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      QUILES, Marcos Gonçalves et al. A network of integrate and fire neurons for visual selection. Neurocomputing, v. 72, n. 10-12, p. 2198-2208, 2009Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2008.10.024. Acesso em: 10 jun. 2024.
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      Quiles, M. G., Liang Zhao,, Breve, F. A., & Romero, R. A. F. (2009). A network of integrate and fire neurons for visual selection. Neurocomputing, 72( 10-12), 2198-2208. doi:10.1016/j.neucom.2008.10.024
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      Quiles MG, Liang Zhao, Breve FA, Romero RAF. A network of integrate and fire neurons for visual selection [Internet]. Neurocomputing. 2009 ; 72( 10-12): 2198-2208.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.neucom.2008.10.024
    • Vancouver

      Quiles MG, Liang Zhao, Breve FA, Romero RAF. A network of integrate and fire neurons for visual selection [Internet]. Neurocomputing. 2009 ; 72( 10-12): 2198-2208.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.neucom.2008.10.024
  • Source: Neurocomputing. Unidade: ICMC

    Subjects: INTELIGÊNCIA ARTIFICIAL, OTIMIZAÇÃO COMBINATÓRIA

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      DELBEM, Alexandre Cláudio Botazzo e CORRÊA, Leonardo Garcia e ZHAO, Liang. Design of associative memories using cellular neural networks. Neurocomputing, v. 72, n. 10-12, p. 2180-2188, 2009Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2008.06.029. Acesso em: 10 jun. 2024.
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      Delbem, A. C. B., Corrêa, L. G., & Zhao, L. (2009). Design of associative memories using cellular neural networks. Neurocomputing, 72( 10-12), 2180-2188. doi:10.1016/j.neucom.2008.06.029
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      Delbem ACB, Corrêa LG, Zhao L. Design of associative memories using cellular neural networks [Internet]. Neurocomputing. 2009 ; 72( 10-12): 2180-2188.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.neucom.2008.06.029
    • Vancouver

      Delbem ACB, Corrêa LG, Zhao L. Design of associative memories using cellular neural networks [Internet]. Neurocomputing. 2009 ; 72( 10-12): 2180-2188.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.neucom.2008.06.029
  • Source: The Journal of Systems and Software. Unidade: ICMC

    Subjects: BANCO DE DADOS, COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS

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      BARIONI, Maria Camila Nardini et al. Accelerating k-medoid-based algorithms through metric access methods. The Journal of Systems and Software, v. 81, n. 6, p. 343-355, 2008Tradução . . Disponível em: https://doi.org/10.1016/j.jss.2007.06.019. Acesso em: 10 jun. 2024.
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      Barioni, M. C. N., Razente, H. L., Traina, A. J. M., & Traina Junior, C. (2008). Accelerating k-medoid-based algorithms through metric access methods. The Journal of Systems and Software, 81( 6), 343-355. doi:10.1016/j.jss.2007.06.019
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      Barioni MCN, Razente HL, Traina AJM, Traina Junior C. Accelerating k-medoid-based algorithms through metric access methods [Internet]. The Journal of Systems and Software. 2008 ; 81( 6): 343-355.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.jss.2007.06.019
    • Vancouver

      Barioni MCN, Razente HL, Traina AJM, Traina Junior C. Accelerating k-medoid-based algorithms through metric access methods [Internet]. The Journal of Systems and Software. 2008 ; 81( 6): 343-355.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.jss.2007.06.019
  • Source: Neurocomputing. Unidades: EACH, ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      OLIVEIRA, Patrícia Rufino e ROMERO, Roseli Aparecida Francelin. Improvements on ICA mixture models for image pre-processing and segmentation. Neurocomputing, v. 71, n. 10-12, p. 2180-2193, 2008Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2007.10.016. Acesso em: 10 jun. 2024.
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      Oliveira, P. R., & Romero, R. A. F. (2008). Improvements on ICA mixture models for image pre-processing and segmentation. Neurocomputing, 71( 10-12), 2180-2193. doi:10.1016/j.neucom.2007.10.016
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      Oliveira PR, Romero RAF. Improvements on ICA mixture models for image pre-processing and segmentation [Internet]. Neurocomputing. 2008 ; 71( 10-12): 2180-2193.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.neucom.2007.10.016
    • Vancouver

      Oliveira PR, Romero RAF. Improvements on ICA mixture models for image pre-processing and segmentation [Internet]. Neurocomputing. 2008 ; 71( 10-12): 2180-2193.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.neucom.2007.10.016
  • Source: Applied Artificial Intelligence. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      ORRU, T. e ROSA, João Luís Garcia e ANDRADE NETTO, Márcio Luiz de. SABio: a biologically plausible connectionist approach to automatic text summarization. Applied Artificial Intelligence, v. 22, n. 9, p. 896-920, 2008Tradução . . Disponível em: http://www.informaworld.com/smpp/title~content=g903561308~db=all. Acesso em: 10 jun. 2024.
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      Orru, T., Rosa, J. L. G., & Andrade Netto, M. L. de. (2008). SABio: a biologically plausible connectionist approach to automatic text summarization. Applied Artificial Intelligence, 22( 9), 896-920. Recuperado de http://www.informaworld.com/smpp/title~content=g903561308~db=all
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      Orru T, Rosa JLG, Andrade Netto ML de. SABio: a biologically plausible connectionist approach to automatic text summarization [Internet]. Applied Artificial Intelligence. 2008 ; 22( 9): 896-920.[citado 2024 jun. 10 ] Available from: http://www.informaworld.com/smpp/title~content=g903561308~db=all
    • Vancouver

      Orru T, Rosa JLG, Andrade Netto ML de. SABio: a biologically plausible connectionist approach to automatic text summarization [Internet]. Applied Artificial Intelligence. 2008 ; 22( 9): 896-920.[citado 2024 jun. 10 ] Available from: http://www.informaworld.com/smpp/title~content=g903561308~db=all
  • Source: Pattern Recognition Letters. Unidade: ICMC

    Assunto: INTELIGÊNCIA ARTIFICIAL

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      CAMPELLO, Ricardo José Gabrielli Barreto. A fuzzy extension of the rand index and other related indexes for clustering and classification assessment. Pattern Recognition Letters, v. 28, n. 7, p. 833-841, 2007Tradução . . Disponível em: https://doi.org/10.1016/j.patrec.2006.11.010. Acesso em: 10 jun. 2024.
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      Campello, R. J. G. B. (2007). A fuzzy extension of the rand index and other related indexes for clustering and classification assessment. Pattern Recognition Letters, 28( 7), 833-841. doi:10.1016/j.patrec.2006.11.010
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      Campello RJGB. A fuzzy extension of the rand index and other related indexes for clustering and classification assessment [Internet]. Pattern Recognition Letters. 2007 ; 28( 7): 833-841.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.patrec.2006.11.010
    • Vancouver

      Campello RJGB. A fuzzy extension of the rand index and other related indexes for clustering and classification assessment [Internet]. Pattern Recognition Letters. 2007 ; 28( 7): 833-841.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.patrec.2006.11.010
  • Source: European Journal of Operational Research. Unidade: ICMC

    Assunto: PESQUISA OPERACIONAL

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      TOLEDO, Franklina Maria Bragion de e ARMENTANO, Vinícius Amaral. A langragian-based heuristic for the capacitated lot-sizing problem in parallel machines. European Journal of Operational Research, v. 175, p. 1070-1083, 2006Tradução . . Disponível em: https://doi.org/10.1016/j.ejor.2005.06.029. Acesso em: 10 jun. 2024.
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      Toledo, F. M. B. de, & Armentano, V. A. (2006). A langragian-based heuristic for the capacitated lot-sizing problem in parallel machines. European Journal of Operational Research, 175, 1070-1083. doi:10.1016/j.ejor.2005.06.029
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      Toledo FMB de, Armentano VA. A langragian-based heuristic for the capacitated lot-sizing problem in parallel machines [Internet]. European Journal of Operational Research. 2006 ;175 1070-1083.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.ejor.2005.06.029
    • Vancouver

      Toledo FMB de, Armentano VA. A langragian-based heuristic for the capacitated lot-sizing problem in parallel machines [Internet]. European Journal of Operational Research. 2006 ;175 1070-1083.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1016/j.ejor.2005.06.029

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