ANN-based optimized design of doubly reinforced rectangular concrete beams based on multi-objective functions

References

• “ACI CODE 318-19: Building Code Requirements for Structural Concrete and Commentary”. 2019
   Google Scholar
• Afshari, H., W. Hare, and S. Tesfamariam. 2019. “Constrained multi-objective Optimization Algorithms: Review and Comparison with Application in Reinforced Concrete Structures.” Applied Soft Computing Journal 83 (July): 105631. doi:10.1016/j.asoc.2019.105631.
   Google Scholar
• Arama, Z. A., A. E. Kayabekir, G. Bekdaş, and Z. W. Geem. 2020. “CO2 and Cost Optimization of Reinforced Concrete Cantilever Soldier Piles: A Parametric Study with Harmony Search Algorithm.” Sustainability 12 (15): 5906. doi:10.3390/su12155906.
   Web of Science ®Google Scholar
• Babaei, M., and M. Mollayi. 2021. “Multiobjective Optimal Design of Reinforced Concrete Frames Using Two Metaheuristic Algorithms.” Journal of Engineering Research (Kuwait) 9 (4 B): 166–192. doi:10.36909/jer.9973.
   Google Scholar
• Barraza, M., E. Bojórquez, E. Fernández-González, and A. Reyes-Salazar. 2017. “Multi-objective Optimization of Structural Steel Buildings under Earthquake Loads Using NSGA-II and PSO.” KSCE Journal of Civil Engineering 21 (2): 488–500. doi:10.1007/s12205-017-1488-7.
   Web of Science ®Google Scholar
• Bekdas, G., and S. M. Nigdeli. 2013. “Optimization of t-shaped RC Flexural Members for Different Compressive Strengths of Concrete.” International Journal of Mechanics 7 (2): 109–119.
   Google Scholar
• Bekdaş, G., and S. M. Nigdeli. 2017. “Modified Harmony Search for Optimization of Reinforced Concrete Frames.” Advances in Intelligent Systems and Computing 514: 213–221. doi:10.1007/978-981-10-3728-3_21.
   Google Scholar
• Brown, N., S. Tseranidis, and C. Mueller (2015). “Multi-objective Optimization for Diversity and Performance in Conceptual Structural Design.” Proceedings of the International Association for Shell and Spatial Structures (IASS) Symposium “Future Visions,” 20, 1–12. https://www.ingentaconnect.com/content/iass/piass/2015/00002015/00000020/art00012 Accessed 9 April 2020)
   Google Scholar
• Brown, N. C. (2016). “Multi-Objective Optimization Conceptual Design of Structures.” Massachusetts Institute of Technology - MSc Thesis, 1–113.
   Google Scholar
• Choi, S. W., B. K. Oh, and H. S. Park. 2017. “Design Technology Based on Resizing Method for Reduction of Costs and Carbon Dioxide Emissions of high-rise Buildings.” Energy and Buildings 138: 612–620. doi:10.1016/j.enbuild.2016.12.095.
   Web of Science ®Google Scholar
• Coello, C. C., F. S. Hernández, and F. A. Farrera. 1997. “Optimal Design of Reinforced Concrete Beams Using Genetic Algorithms.” Expert Systems with Applications 12 (1): 101–108. doi:10.1016/S0957-4174(96)00084-X.
   Web of Science ®Google Scholar
• Deb, K., A. Pratap, S. Agarwal, and T. Meyarivan. 2002. “A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II.” IEEE Transactions on Evolutionary Computation 6 (2): 182–197. doi:10.1109/4235.996017.
   Web of Science ®Google Scholar
• Ferreira, C. C., M. H. F. M. Barros, and A. F. M. Barros. 2003. “Optimal Design of Reinforced Concrete T-sections in Bending.” Engineering Structures 25 (7): 951–964. doi:10.1016/S0141-0296(03)00039-7.
   Web of Science ®Google Scholar
• Ferreira, F. P. V., R. Shamass, V. Limbachiya, K. D. Tsavdaridis, and C. H. Martins. 2022. “Lateral–torsional Buckling Resistance Prediction Model for Steel Cellular Beams Generated by Artificial Neural Networks (ANN).” Thin-Walled Structures 170 (September 2021): 108592. doi:10.1016/j.tws.2021.108592.
   Google Scholar
• Hong, W.-K., J.-M. Kim, S.-C. Park, S.-G. Lee, S.-I. Kim, K.-J. Yoon, H.-C. Kim, and J. T. Kim. 2010. “A New Apartment Construction Technology with Effective CO2 Emission Reduction Capabilities.” Energy 35 (6): 2639–2646. doi:10.1016/j.energy.2009.05.036.
   Web of Science ®Google Scholar
• Hong, W.-K. 2020. “Chapter 10 - Artificial-intelligence-based Design of the Ductile Precast Concrete Beams.” In Woodhead Publishing Series in Civil and Structural Engineering, edited by W.-K. B. T.-H. C. P. S. Hong, 427–478. Sawston, Cambridge: Woodhead Publishing. doi:10.1016/B978-0-08-102721-9.00010-8.
   Google Scholar
• Hong, W.-K., and M. C. Nguyen. 2021. “AI-based Lagrange Optimization for Designing Reinforced Concrete Columns.” Journal of Asian Architecture and Building Engineering 1–15. doi:10.1080/13467581.2021.1971998.
   Web of Science ®Google Scholar
• Hong, W.-K., V. T. Nguyen, and M. C. Nguyen. 2021. “Optimizing Reinforced Concrete Beams Cost Based on AI-based Lagrange Functions”. Journal of Asian Architecture and Building Engineering, no. ja. doi:10.1080/13467581.2021.2007105.
   Google Scholar
• Hong, W. K., T. A. Le, M. C. Nguyen, and T. D. Pham 2022 . “ANN-based Lagrange optimization for RC circular columns having multi-objective functions.” Journal of Asian Architecture and Building Engineering doi:10.1080/13467581.2022.2064864.
   Web of Science ®Google Scholar
• Hosseinpour, M., Y. Sharifi, and H. Sharifi. 2020. “Neural Network Application for Distortional Buckling Capacity Assessment of Castellated Steel Beams.” Structures 27: 1174–1183. doi:10.1016/j.istruc.2020.07.027.
   Web of Science ®Google Scholar
• Jaeggi, D., G. Parks, T. Kipouros, and J. Clarkson. 2005. A Multi-objective Tabu Search Algorithm for Constrained Optimisation Problems BT - Evolutionary Multi-Criterion Optimization, eds. C. A. C. Coello, A. H. Aguirre, and E. Zitzler., 490–504. Berlin Heidelberg: Springer.
   Google Scholar
• Jahjouh, M. M., M. H. Arafa, and M. A. Alqedra. 2013. “Artificial Bee Colony (ABC) Algorithm in the Design Optimization of RC Continuous Beams.” Structural and Multidisciplinary Optimization 47 (6): 963–979. doi:10.1007/s00158-013-0884-y.
   Web of Science ®Google Scholar
• Karush, W. (1939). “Minima of Functions of Several Variables with Inequalities as Side Constraints” (M.Sc. thesis). Dept. of Mathematics, Univ. of Chicago, Chicago, Illinois.
   Google Scholar
• Kaveh, A., and O. Sabzi. 2012. “Optimal Design of Reinforced Concrete Frames Using Big bang-big Crunch Algorithm.” International Journal of Civil Engineering 10 (3): 189–200.
   Web of Science ®Google Scholar
• Kaveh, A., and V. R. Mahdavi. 2019. “Multi-objective Colliding Bodies Optimization Algorithm for Design of Trusses.” Journal of Computational Design and Engineering 6 (1): 49–59. doi:10.1016/j.jcde.2018.04.001.
   Web of Science ®Google Scholar
• Kayabekir, A. E., Z. A. Arama, G. Bekdaş, S. M. Nigdeli, and Z. W. Geem. 2020. “Eco-Friendly Design of Reinforced Concrete Retaining Walls: Multi-objective Optimization with Harmony Search Applications.” Sustainability 12 (15): 6087. doi:10.3390/su12156087.
   Web of Science ®Google Scholar
• Kuhn, H. W., and A. W. Tucker (1951). “Nonlinear Programming”. Proceedings of 2nd Berkeley Symposium. Berkeley: University of California Press. pp. 481–492.
   Google Scholar
• Lee, M.-S., K. Hong, and S.-W. Choi. nd. “Genetic Algorithm Based Optimal Structural Design Method for Cost and CO2 Emissions of Reinforced Concrete Frames TT - 철근콘크리트 모멘트골조의 비용 및 이산화탄소 배출량을 고려한 유전자알고리즘 기반 구조최적화기법.” Journal of the Computational Structural Engineering Institute of Korea 29 (5): 429–436. doi:10.7734/COSEIK.2016.29.5.429.
   Google Scholar
• Liu, X., and A. C. Reynolds. 2016. “Gradient-based multi-objective Optimization with Applications to Waterflooding Optimization.” Computational Geosciences 20 (3): 677–693. doi:10.1007/s10596-015-9523-6.
   Web of Science ®Google Scholar
• Marler, R. T., and J. S. Arora. 2004. “Survey of multi-objective Optimization Methods for Engineering.” Structural and Multidisciplinary Optimization 26 (6): 369–395. doi:10.1007/s00158-003-0368-6.
   Web of Science ®Google Scholar
• Martinez-Martin, F. J., F. Gonzalez-Vidosa, A. Hospitaler, and V. Yepes. 2012. “Multi-objective Optimization Design of Bridge Piers with Hybrid Heuristic Algorithms.” Journal of Zhejiang University: Science A 13 (6): 420–432. doi:10.1631/jzus.A1100304.
   Web of Science ®Google Scholar
• MathWorks. 2020b. MATLAB R2020b, Version 9.9.0. Natick, MA: MathWorks.
   Google Scholar
• Mei, L., and Q. Wang. 2021. “Structural Optimization in Civil Engineering: A Literature Review.” Buildings 11 (2): 1–28. doi:10.3390/buildings11020066.
   Web of Science ®Google Scholar
• Mohd Zain, M. Z. B., J. Kanesan, J. H. Chuah, S. Dhanapal, and G. Kendall. 2018. “A multi-objective Particle Swarm Optimization Algorithm Based on Dynamic Boundary Search for Constrained Optimization.” Applied Soft Computing Journal 70: 680–700. doi:10.1016/j.asoc.2018.06.022.
   Web of Science ®Google Scholar
• Munk, D. J., G. A. Vio, and G. P. Steven. 2015. “Topology and Shape Optimization Methods Using Evolutionary Algorithms: A Review.” Structural and Multidisciplinary Optimization 52 (3): 613–631. doi:10.1007/s00158-015-1261-9.
   Web of Science ®Google Scholar
• Nan, B., Y. Bai, and Y. Wu. 2020. “Multi-objective Optimization of Spatially Truss Structures Based on Node Movement.” Applied Sciences (Switzerland) 10 (6). doi:10.3390/app10061964.
   Google Scholar
• Nguyen, D. H., and W. K. Hong. 2019. “Part I: The Analytical Model Predicting post-yield Behavior of concrete-encased Steel Beams considering Various Confinement Effects by Transverse Reinforcements and Steels.” Materials 12 (14): 2302. doi:10.3390/ma12142302.
   PubMed Web of Science ®Google Scholar
• Nguyen, T.-A., H.-B. Ly, and V. Q. Tran. 2021. “Investigation of ANN Architecture for Predicting Load-Carrying Capacity of Castellated Steel Beams.” Complexity 2021: 6697923. doi:10.1155/2021/6697923.
   Web of Science ®Google Scholar
• Park, H. S., B. Kwon, Y. Shin, Y. Kim, T. Hong, and S. W. Choi. 2013. “Cost and CO2 Emission Optimization of Steel Reinforced Concrete Columns in high-rise Buildings.” Energies 6 (11): 5609–5624. doi:10.3390/en6115609.
   Web of Science ®Google Scholar
• Shaqfa, M., and Z. Orbán. 2019. “Modified parameter-setting-free Harmony Search (PSFHS) Algorithm for Optimizing the Design of Reinforced Concrete Beams.” Structural and Multidisciplinary Optimization 60 (3): 999–1019. doi:10.1007/s00158-019-02252-4.
   Web of Science ®Google Scholar
• Sharifi, Y., A. Moghbeli, M. Hosseinpour, and H. Sharifi. 2020. “Study of Neural Network Models for the Ultimate Capacities of Cellular Steel Beams.” Iranian Journal of Science and Technology, Transactions of Civil Engineering 44 (2): 579–589. doi:10.1007/s40996-019-00281-z.
   Web of Science ®Google Scholar
• Tahmassebi, A., B. Mohebali, A. Meyer‐Baese, and A. H. Gandomi. 2020. “Multiobjective Genetic Programming for Reinforced Concrete Beam Modeling.” Applied AI Letters 1 (1): 1–10. doi:10.1002/ail2.9.
   Google Scholar
• Yang, X.-S. 2014. “Chapter 14 - Multi-Objective Optimization.” In Nature-Inspired Optimization Algorithms, edited by X.-S. Yang, 197–211. Amsterdam: Elsevier. doi:10.1016/B978-0-12-416743-8.00014-2.
   Google Scholar
• Yücel, M., G. Bekdaş, S. M. Nigdeli, and A. E. Kayabekir. 2021a. “An Artificial Intelligence-Based Prediction Model for Optimum Design Variables of Reinforced Concrete Retaining Walls.” International Journal of Geomechanics 21 (12): 1–10. doi:10.1061/(asce)gm.1943-5622.0002234.
   Web of Science ®Google Scholar
• Yücel, M., S. M. Nigdeli, A. E. Kayabekir, and G. Bekdaş. 2021b. “Optimization and Artificial Neural Network Models for Reinforced Concrete Members.” In Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications, edited by S. Carbas, A. Toktas, and D. Ustun, 181–199. Singapore: Springer Singapore. doi:10.1007/978-981-33-6773-9_9.
   Google Scholar
• Zhang, Z.-Y., Z. Gifari, Y.-K. Ju, and J. H. Kim (2021). “Multi-objective Optimization of the Reinforced Concrete Beam.” In S. M. Nigdeli, J. H. Kim, G. Bekdaş, and A. Yadav (Eds.), Proceedings of 6th International Conference on Harmony Search, Soft Computing and Applications (pp. 171–178). Springer Singapore.
   Google Scholar
• Zheng, Y. G., and X. X. Hu (2018). “Multi-objective Optimal Design on Vibration Suppression of Building Structures with Active Mass Damper Based on State Difference Feedback.” Chinese Control Conference, CCC (China), 2018-July,1249–1253. 10.23919/ChiCC.2018.8482723
   Google Scholar
• Zheng, X., D. Zhou, N. Li, T. Wu, Y. Lei, and J. Shi. 2021. “Self-Regulated Particle Swarm Multi-Task Optimization.” Sensors 21 (22): 7499. doi:10.3390/s21227499.
   PubMed Web of Science ®Google Scholar