Diseño automático de cerchas de gran escala: una comparación entre algoritmos libres de derivadas
Main Article Content
Keywords
Optimización metaheurística multiobjetivo, estructuras articuladas, cercha, gran escala
Resumen
El diseño de estructuras metálicas tipo cercha es un problema frecuente en la ingeniería civil, que requiere de la experiencia del ingeniero diseñador para lograr una solución estructural con buen desempeño y que pueda satisfacer las necesidades establecidas. En los últimos años, el diseño de estos sistemas ha sido soportado mediante la aplicación de diversos métodos de optimización, que permiten obtener soluciones óptimas, dando cumplimiento a los objetivos de diseño propuestos, de forma automática y en un menor tiempo de trabajo. Esta investigación presenta la aplicación de una serie de algoritmos metaheurísticos multiobjetivo para el diseño automático de cerchas de gran escala. Se aplicaron los algoritmos NSGA-II, MOPSO y AMOSA y se consideraron estructuras reportadas en la literatura conformadas por un número elevado de elementos. El desempeño de los algoritmos se evaluó con base en el costo computacional, el criterio del hipervolumen y el comportamiento que tienen los algoritmos al aumentar la cantidad de iteraciones por ciclo de optimización. El espacio de búsqueda usado en la optimización fue discreto, restringido por los perles de acero W disponibles en el mercado colombiano. Los resultados obtenidos demuestran que, para los problemas propuestos, el algoritmo MOPSO es el más eficiente, seguido del AMOSA y del NSGA-II que mostró un costo computacional mayor. Finalmente, vale la pena mencionar que los tiempos de cálculo fueron menores a una hora, para cerchas cercanas a los mil elementos.
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Referencias
[1] H. Assimi and A. Jamali, “A hybrid algorithm coupling genetic programming and nelder - mead for topology and size optimization of trusses with static and dynamic constraints,” Expert Systems with Applications, vol. 95, pp. 127–141, 2018. https://doi.org/10.1016/j.eswa.2017.11.035
[2] O. Hasançebi, “Adaptive evolution strategies in structural optimization: Enhancing their computational performance with applications to large-scale structures,” Computers and Structures, vol. 86, no. 1-2, pp. 119–132, 2008. https://doi.org/10.1016/j.compstruc.2007.05.012
[3] O. Hasançebi and S. K. Azad, “Adaptive dimensional search: A new metaheuristic algorithm for discrete truss sizing optimization,” Computers and Structures, vol. 154, pp. 1–16, 2015. https://doi.org/10.1016/j.compstruc.2015.03.014
[4] S. Degertekin, L. Lamberti, and I. Ugur, “Discrete sizing/layout/topology optimization of truss structures with an advanced jaya algorithm,” Applied Soft Computing Journal, vol. 79, pp. 363–390, 2019. https://doi.org/10.1016/j.asoc.2019.03.058
[5] K. Deb and S. Gulati, “Design of truss-structures for minimum weight using genetic algorithms,” Finite Elements in Analysis and Design, vol. 37, no. 5, pp. 447–465, may 2001. https://doi.org/10.1016/S0168-74X(00)00057-3
[6] G. G. Tejani, V. J. Savsani, V. K. Patel, and P. V. Savsani, “Size, shape, and topology optimization of planar and space trusses using mutation-based improved metaheuristics,” Journal of Computational Design and Engineering, vol. 5, no. 2, pp. 198–214, 10 2017. https://doi.org/10.1016/j.jcde.2017.10.001
[7] H. Cao, X. Qian, and Y. Zhou, “Large-scale structural optimization using metaheuristic algorithms with elitism and a filter strategy,” Structural and Multidisciplinary Optimization, vol. 57, no. 2, pp. 799–814, feb 2018. https://doi.org/10.1007/s00158-017-1784-3
[8] M. Khatibinia and H. Yazdani, “Accelerated multi-gravitational search algorithm for size optimization of truss structures,” Swarm and Evolutionary Computation, vol. 38, no. June 2017, pp. 109–119, 2018. https://doi.org/10.1016/j.swevo.2017.07.001
[9] H. Assimi, A. Jamali, and N. Nariman-zadeh, “Sizing and topology optimization of truss structures using genetic programming,” Swarm and Evolutionary Computation, vol. 37, pp. 90–103, dec 2017. https://doi.org/10.1016/j.swevo.2017.05.009
[10] M. S. Gonçalves, R. H. Lopez, and L. F. F. Miguel, “Search group algorithm: A new metaheuristic method for the optimization of truss structures,” Computers and Structures, vol. 153, pp. 165–184, 2015. https://doi.org/10.1016/j.compstruc.2015.03.003
[11] L. F. F. Miguel, R. H. Lopez, and L. F. F. Miguel, “Multimodal size, shape, and topology optimisation of truss structures using the firefly algorithm,” Advances in Engineering Software, vol. 56, pp. 23–37, 2013. https://doi.org/10.1016/j.advengsoft.2012.11.006
[12] A. Kaveh and M. Ilchi Ghazaan, Meta-heuristic Algorithms for Optimal Design of Real-Size Structures, 1st ed. Cham: Springer International Publishing, 2018. https://doi.org/10.1007/978-3-319-78780-0
[13] I. Couceiro, J. París, S. Martínez, I. Colominas, F. Navarrina, and M. Casteleiro, “Structural optimization of lattice steel transmission towers,” Engineering Structures, vol. 117, pp. 274–286, 2016. https://doi.org/10.1016/j.engstruct.2016.03.005
[14] C. Tort, S. Sahin, and O. Hasançebi, “Optimum design of steel lattice transmission line towers using simulated annealing and pls-tower,” Computers & Structures, vol. 179, pp. 75–94, 2017.
[15] R. R. de Souza, L. F. F. Miguel, R. H. Lopez, L. F. F. Miguel, and A. J. Torii, “A procedure for the size, shape and topology optimization of transmission line tower structures,” Engineering Structures, vol. 111, pp. 162–184, 2016. https://doi.org/10.1016/j.engstruct.2015.12.005
[16] S. Degertekin, L. Lamberti, and I. Ugur, “Sizing, layout and topology design optimization of truss structures using the Jaya algorithm,” Applied Soft Computing Journal, 2017. https://doi.org/10.1016/j.asoc.2017.10.001
[17] S. Gholizadeh and A. Baghchevan, “Multi-objective seismic design optimization of steel frames by a chaotic meta-heuristic algorithm,” Engineering with Computers, vol. 33, no. 4, pp. 1045–1060, oct 2017. https://doi.org/10.1007/s00366-017-0515-0
[18] V. Mokarram and M. R. Banan, “A new PSO-based algorithm for multi-objective optimization with continuous and discrete design variables,” Structural and Multidisciplinary Optimization, vol. 57, no. 2, pp. 509–533, 2018. https://doi.org/10.1007/s00158-017-1764-7
[19] K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, “A fast and elitist multiobjective genetic algorithm: NSGA-II,” IEEE Transactions on Evolutionary Computation, vol. 6, no. 2, pp. 182–197, apr 2002. https://doi.org/10.1109/4235.996017
[20] C. C. Coello and M. S. Lechuga, “Mopso: A proposal for multiple objective particle swarm optimization,” in Proceedings of the 2002 Congress on Evolutionary Computation. CEC’02 (Cat. No. 02TH8600), vol. 2. IEEE, 2002, pp. 1051–1056.
[21] C. A. Coello Coello, G. Toscano Pulido, and M. Salazar Lechuga, “Handling multiple objectives with particle swarm optimization,” IEEE Transactions on evolutionary computation, vol. 8, no. 3, pp. 256–279, 2004. https://doi.org/10.1109/TEVC.2004.826067
[22] S. Bandyopadhyay, S. Saha, U. Maulik, and K. Deb, “A simulated annealing-based multiobjective optimization algorithm: Amosa,” IEEE transactions on evolutionary computation, vol. 12, no. 3, pp. 269–283, 2008. https://doi.org/10.1109/TEVC.2007.900837
[23] A. Kaveh and S. Talatahari, “A particle swarm ant colony optimization for truss structures with discrete variables,” Journal of Constructional Steel Research, vol. 65, no. 8-9, pp. 1558–1568, 2009. https://doi.org/10.1016/j.jcsr.2009.04.021
[24] A. Kaveh and M. Khayatazad, “Ray optimization for size and shape optimization of truss structures,” Computers and Structures, vol. 117, pp. 82–94, 2013. https://doi.org/10.1016/j.compstruc.2012.12.010
[25] A. Kaveh and A. Zolghadr, “Comparison of nine meta-heuristic algorithms for optimal design of truss structures with frequency constraints,” Advances in Engineering Software, vol. 76, pp. 9–30, 2014. https://doi.org/10.1016/j.advengsoft.2014.05.012
[26] A. Kaveh and V. R. Mahdavi, “Colliding Bodies Optimization method for optimum discrete design of truss structures,” Computers and Structures, vol. 139, pp. 43–53, 2014.
http://dx.doi.org/10.1016/j.compstruc.2014.04.006
[27] A. Mortazavi and V. Togan, “Simultaneous size, shape, and topology optimization of truss structures using integrated particle swarm optimizer,” Structural and Multidisciplinary Optimization, vol. 54, no. 4, pp. 715–736,
2016. https://doi.org/10.1007/s00158-016-1449-7
[28] A. Mortazavi and V. Togan, “Sizing and layout design of truss structures under dynamic and static constraints with an integrated particle swarm optimization algorithm,” Applied Soft Computing Journal, vol. 51, pp. 239–252, 2017. https://doi.org/10.1016/j.asoc.2016.11.032
[29] G. Bekdas, S. M. Nigdeli, and X. S. Yang, “Sizing optimization of truss structures using flower pollination algorithm,” Applied Soft Computing Journal, vol. 37, pp. 322–331, 2015. https://doi.org/10.1016/j.asoc.2015.08.037
[30] E.-G. Talbi, Metaheuristics: from design to implementation. John Wiley & Sons, 2009, vol. 74. 87
[31] P. Ngatchou, A. Zarei, and A. El-Sharkawi, “Pareto multi objective optimization,” in Proceedings of the 13th International Conference on, Intelligent Systems Application to Power Systems. IEEE, 2005, pp. 84–91.
[32] K. Deb, Multi-objective optimization using evolutionary algorithms. John Wiley & Sons, 2001, vol. 16.
[33] J. S. Arora, “Optimum Design Problem Formulation,” in Introduction to Optimum Design, 4th ed. Elsevier, 2017, pp. 19–70.
[34] K. L. Du, M. Swamy et al., “Search and optimization by metaheuristics,” Techniques and Algorithms Inspired by Nature; Birkhauser: Basel, Switzerland, 2016.
[35] MATLAB, “version 9.6.0 (2019a),” Natick, Massachusetts, 2019.
[36] M. Y. Cheng, D. Prayogo, Y. W. Wu, and M. M. Lukito, “A Hybrid Harmony Search algorithm for discrete sizing optimization of truss structure,” Automation in Construction, vol. 69, pp. 21–33, 2016. https://doi.org/10.1016/j.autcon.2016.05.023
[37] S. Fallahian, D. Hamidian, and S. M. Seyedpoor, “Optimal Design of Structures using the simultaneous perturbation stochastic approximation algorithm,” International Journal of Computational Methods, vol. 6, no. 2,
pp. 229–245, 2009. https://doi.org/10.1002/0471722138.ch7
[38] K. S. Lee and Z. W. Geem, “A new structural optimization method based on the harmony search algorithm,” Computers & structures, vol. 82, no. 9-10, pp. 781–798, 2004. https://doi.org/10.1016/j.compstruc.2004.01.002
[2] O. Hasançebi, “Adaptive evolution strategies in structural optimization: Enhancing their computational performance with applications to large-scale structures,” Computers and Structures, vol. 86, no. 1-2, pp. 119–132, 2008. https://doi.org/10.1016/j.compstruc.2007.05.012
[3] O. Hasançebi and S. K. Azad, “Adaptive dimensional search: A new metaheuristic algorithm for discrete truss sizing optimization,” Computers and Structures, vol. 154, pp. 1–16, 2015. https://doi.org/10.1016/j.compstruc.2015.03.014
[4] S. Degertekin, L. Lamberti, and I. Ugur, “Discrete sizing/layout/topology optimization of truss structures with an advanced jaya algorithm,” Applied Soft Computing Journal, vol. 79, pp. 363–390, 2019. https://doi.org/10.1016/j.asoc.2019.03.058
[5] K. Deb and S. Gulati, “Design of truss-structures for minimum weight using genetic algorithms,” Finite Elements in Analysis and Design, vol. 37, no. 5, pp. 447–465, may 2001. https://doi.org/10.1016/S0168-74X(00)00057-3
[6] G. G. Tejani, V. J. Savsani, V. K. Patel, and P. V. Savsani, “Size, shape, and topology optimization of planar and space trusses using mutation-based improved metaheuristics,” Journal of Computational Design and Engineering, vol. 5, no. 2, pp. 198–214, 10 2017. https://doi.org/10.1016/j.jcde.2017.10.001
[7] H. Cao, X. Qian, and Y. Zhou, “Large-scale structural optimization using metaheuristic algorithms with elitism and a filter strategy,” Structural and Multidisciplinary Optimization, vol. 57, no. 2, pp. 799–814, feb 2018. https://doi.org/10.1007/s00158-017-1784-3
[8] M. Khatibinia and H. Yazdani, “Accelerated multi-gravitational search algorithm for size optimization of truss structures,” Swarm and Evolutionary Computation, vol. 38, no. June 2017, pp. 109–119, 2018. https://doi.org/10.1016/j.swevo.2017.07.001
[9] H. Assimi, A. Jamali, and N. Nariman-zadeh, “Sizing and topology optimization of truss structures using genetic programming,” Swarm and Evolutionary Computation, vol. 37, pp. 90–103, dec 2017. https://doi.org/10.1016/j.swevo.2017.05.009
[10] M. S. Gonçalves, R. H. Lopez, and L. F. F. Miguel, “Search group algorithm: A new metaheuristic method for the optimization of truss structures,” Computers and Structures, vol. 153, pp. 165–184, 2015. https://doi.org/10.1016/j.compstruc.2015.03.003
[11] L. F. F. Miguel, R. H. Lopez, and L. F. F. Miguel, “Multimodal size, shape, and topology optimisation of truss structures using the firefly algorithm,” Advances in Engineering Software, vol. 56, pp. 23–37, 2013. https://doi.org/10.1016/j.advengsoft.2012.11.006
[12] A. Kaveh and M. Ilchi Ghazaan, Meta-heuristic Algorithms for Optimal Design of Real-Size Structures, 1st ed. Cham: Springer International Publishing, 2018. https://doi.org/10.1007/978-3-319-78780-0
[13] I. Couceiro, J. París, S. Martínez, I. Colominas, F. Navarrina, and M. Casteleiro, “Structural optimization of lattice steel transmission towers,” Engineering Structures, vol. 117, pp. 274–286, 2016. https://doi.org/10.1016/j.engstruct.2016.03.005
[14] C. Tort, S. Sahin, and O. Hasançebi, “Optimum design of steel lattice transmission line towers using simulated annealing and pls-tower,” Computers & Structures, vol. 179, pp. 75–94, 2017.
[15] R. R. de Souza, L. F. F. Miguel, R. H. Lopez, L. F. F. Miguel, and A. J. Torii, “A procedure for the size, shape and topology optimization of transmission line tower structures,” Engineering Structures, vol. 111, pp. 162–184, 2016. https://doi.org/10.1016/j.engstruct.2015.12.005
[16] S. Degertekin, L. Lamberti, and I. Ugur, “Sizing, layout and topology design optimization of truss structures using the Jaya algorithm,” Applied Soft Computing Journal, 2017. https://doi.org/10.1016/j.asoc.2017.10.001
[17] S. Gholizadeh and A. Baghchevan, “Multi-objective seismic design optimization of steel frames by a chaotic meta-heuristic algorithm,” Engineering with Computers, vol. 33, no. 4, pp. 1045–1060, oct 2017. https://doi.org/10.1007/s00366-017-0515-0
[18] V. Mokarram and M. R. Banan, “A new PSO-based algorithm for multi-objective optimization with continuous and discrete design variables,” Structural and Multidisciplinary Optimization, vol. 57, no. 2, pp. 509–533, 2018. https://doi.org/10.1007/s00158-017-1764-7
[19] K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, “A fast and elitist multiobjective genetic algorithm: NSGA-II,” IEEE Transactions on Evolutionary Computation, vol. 6, no. 2, pp. 182–197, apr 2002. https://doi.org/10.1109/4235.996017
[20] C. C. Coello and M. S. Lechuga, “Mopso: A proposal for multiple objective particle swarm optimization,” in Proceedings of the 2002 Congress on Evolutionary Computation. CEC’02 (Cat. No. 02TH8600), vol. 2. IEEE, 2002, pp. 1051–1056.
[21] C. A. Coello Coello, G. Toscano Pulido, and M. Salazar Lechuga, “Handling multiple objectives with particle swarm optimization,” IEEE Transactions on evolutionary computation, vol. 8, no. 3, pp. 256–279, 2004. https://doi.org/10.1109/TEVC.2004.826067
[22] S. Bandyopadhyay, S. Saha, U. Maulik, and K. Deb, “A simulated annealing-based multiobjective optimization algorithm: Amosa,” IEEE transactions on evolutionary computation, vol. 12, no. 3, pp. 269–283, 2008. https://doi.org/10.1109/TEVC.2007.900837
[23] A. Kaveh and S. Talatahari, “A particle swarm ant colony optimization for truss structures with discrete variables,” Journal of Constructional Steel Research, vol. 65, no. 8-9, pp. 1558–1568, 2009. https://doi.org/10.1016/j.jcsr.2009.04.021
[24] A. Kaveh and M. Khayatazad, “Ray optimization for size and shape optimization of truss structures,” Computers and Structures, vol. 117, pp. 82–94, 2013. https://doi.org/10.1016/j.compstruc.2012.12.010
[25] A. Kaveh and A. Zolghadr, “Comparison of nine meta-heuristic algorithms for optimal design of truss structures with frequency constraints,” Advances in Engineering Software, vol. 76, pp. 9–30, 2014. https://doi.org/10.1016/j.advengsoft.2014.05.012
[26] A. Kaveh and V. R. Mahdavi, “Colliding Bodies Optimization method for optimum discrete design of truss structures,” Computers and Structures, vol. 139, pp. 43–53, 2014.
http://dx.doi.org/10.1016/j.compstruc.2014.04.006
[27] A. Mortazavi and V. Togan, “Simultaneous size, shape, and topology optimization of truss structures using integrated particle swarm optimizer,” Structural and Multidisciplinary Optimization, vol. 54, no. 4, pp. 715–736,
2016. https://doi.org/10.1007/s00158-016-1449-7
[28] A. Mortazavi and V. Togan, “Sizing and layout design of truss structures under dynamic and static constraints with an integrated particle swarm optimization algorithm,” Applied Soft Computing Journal, vol. 51, pp. 239–252, 2017. https://doi.org/10.1016/j.asoc.2016.11.032
[29] G. Bekdas, S. M. Nigdeli, and X. S. Yang, “Sizing optimization of truss structures using flower pollination algorithm,” Applied Soft Computing Journal, vol. 37, pp. 322–331, 2015. https://doi.org/10.1016/j.asoc.2015.08.037
[30] E.-G. Talbi, Metaheuristics: from design to implementation. John Wiley & Sons, 2009, vol. 74. 87
[31] P. Ngatchou, A. Zarei, and A. El-Sharkawi, “Pareto multi objective optimization,” in Proceedings of the 13th International Conference on, Intelligent Systems Application to Power Systems. IEEE, 2005, pp. 84–91.
[32] K. Deb, Multi-objective optimization using evolutionary algorithms. John Wiley & Sons, 2001, vol. 16.
[33] J. S. Arora, “Optimum Design Problem Formulation,” in Introduction to Optimum Design, 4th ed. Elsevier, 2017, pp. 19–70.
[34] K. L. Du, M. Swamy et al., “Search and optimization by metaheuristics,” Techniques and Algorithms Inspired by Nature; Birkhauser: Basel, Switzerland, 2016.
[35] MATLAB, “version 9.6.0 (2019a),” Natick, Massachusetts, 2019.
[36] M. Y. Cheng, D. Prayogo, Y. W. Wu, and M. M. Lukito, “A Hybrid Harmony Search algorithm for discrete sizing optimization of truss structure,” Automation in Construction, vol. 69, pp. 21–33, 2016. https://doi.org/10.1016/j.autcon.2016.05.023
[37] S. Fallahian, D. Hamidian, and S. M. Seyedpoor, “Optimal Design of Structures using the simultaneous perturbation stochastic approximation algorithm,” International Journal of Computational Methods, vol. 6, no. 2,
pp. 229–245, 2009. https://doi.org/10.1002/0471722138.ch7
[38] K. S. Lee and Z. W. Geem, “A new structural optimization method based on the harmony search algorithm,” Computers & structures, vol. 82, no. 9-10, pp. 781–798, 2004. https://doi.org/10.1016/j.compstruc.2004.01.002
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nov 11, 2020
Article Details
Cómo citar
Niño-Alvarez, L., Guevara-Corzo, J., & Begambre-Carrillo, O. (2020). Diseño automático de cerchas de gran escala: una comparación entre algoritmos libres de derivadas. Ingeniería Y Ciencia, 16(32), 83–108. https://doi.org/10.17230/ingciencia.16.32.4
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Universidad Industrial de Santander
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