Geomechanics and Engineering

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Optimum design of cantilever retaining walls under seismic loads using a hybrid TLBO algorithm

  • Temur, Rasim (Department of Civil Engineering, Istanbul University-Cerrahpasa)
  • Received : 2020.06.11
  • Accepted : 2021.01.20
  • Published : 2021.02.10
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Abstract

The main purpose of this study is to investigate the performance of the proposed hybrid teaching-learning based optimization algorithm on the optimum design of reinforced concrete (RC) cantilever retaining walls. For this purpose, three different design examples are optimized with 100 independent runs considering continuous and discrete variables. In order to determine the algorithm performance, the optimization results were compared with the outcomes of the nine powerful meta-heuristic algorithms applied to this problem, previously: the big bang-big crunch (BB-BC), the biogeography based optimization (BBO), the flower pollination (FPA), the grey wolf optimization (GWO), the harmony search (HS), the particle swarm optimization (PSO), the teaching-learning based optimization (TLBO), the jaya (JA), and Rao-3 algorithms. Moreover, Rao-1 and Rao-2 algorithms are applied to this design problem for the first time. The objective function is defined as minimizing the total material and labor costs including concrete, steel, and formwork per unit length of the cantilever retaining walls subjected to the requirements of the American Concrete Institute (ACI 318-05). Furthermore, the effects of peak ground acceleration value on minimum total cost is investigated using various stem height, surcharge loads, and backfill slope angle. Finally, the most robust results were obtained by HTLBO with 50 populations. Consequently the optimization results show that, depending on the increase in PGA value, the optimum cost of RC cantilever retaining walls increases smoothly with the stem height but increases rapidly with the surcharge loads and backfill slope angle.

Keywords

References

  1. ACI 318-05 (2004), Building Code Requirements for Structural Concrete and Commentary, American Concrete Institute.
  2. Akin, A. and Saka, M.P. (2015), "Harmony search algorithm based optimum detailed design of reinforced concrete plane frames subject to ACI 318-05 provisions", Comput. Struct., 147, 79-95. https:/doi.org/10.1016/j.compstruc.2014.10.003.
  3. Aydogdu, I. (2017), "Cost optimization of reinforced concrete cantilever retaining walls under seismic loading using a biogeography-based optimization algorithm with Levy flights", Eng. Optimiz., 49(3), 381-400. https:/doi.org/10.1080/0305215x.2016.1191837.
  4. Bekdas, G. and Temur, R. (2018), "Grey wolf optimizer for optimum design of reinforced concrete cantilever retaining walls", Proceedings of the International Conference of Numerical Analysis and Applied Mathematics, Rhodes, Greece, September.
  5. Camp, C.V. and Akin, A. (2012), "Design of retaining walls using big bang-big crunch optimization", J. Struct. Eng., 138(3), 438-448. https:/doi.org/10.1061/(Asce)St.1943-541x.0000461.
  6. Ceranic, B., Fryer, C. and Baines, R.W. (2001), "An application of simulated annealing to the optimum design of reinforced concrete retaining structures", Comput. Struct., 79(17), 1569-1581. https:/doi.org/10.1016/S0045-7949(01)00037-2.
  7. Chan, C.M., Zhang, L.M. and Ng, J.T.M. (2009), "Optimization of pile groups using hybrid genetic algorithms", J. Geotech. Geoenviron. Eng., 135(4), 497-505. https:/doi.org/10.1061/(ASCE)1090-0241(2009)135:4(497).
  8. Chaudhuri, P. and Maity, D. (2020), "Cost optimization of rectangular RC footing using GA and UPSO", Soft Comput., 24(2), 709-721. https:/doi.org/10.1007/s00500-019-04437-x.
  9. Christopher, B.R., Gill, S., Giroud, J.-P., Juran, I., Mitchell, J.K., Schlosser, F. and Dunnicliff, J. (1990), Reinforced soil Structures, Volume I, Design and Construction Guidelines, Federal Highway Administration, U.S.A.
  10. Coulomb, C.A. (1776), "Essai sur une application des regles des maximis et minimis a quelques problemes de statique relatifs a l'architecture [Test on an application of the rules of maxima and minima to some problems of statics related to architecture]", Memoires de l'Academie Royal Pres Divers Savants, 7, 343-382.
  11. El Semelawy, M., Nassef, A.O. and El Damatty, A.A. (2012), "Design of prestressed concrete flat slab using modern heuristic optimization techniques", Expert Syst. Appl., 39(5), 5758-5766. https:/doi.org/10.1016/j.eswa.2011.11.093.
  12. Gandomi, A.H., Kashani, A.R., Roke, D.A. and Mousavi, M. (2015), "Optimization of retaining wall design using recent swarm intelligence techniques", Eng. Struct., 103, 72-84. https:/doi.org/10.1016/j.engstruct.2015.08.034.
  13. Gandomi, A.H., Kashani, A.R., Roke, D.A. and Mousavi, M. (2017), "Optimization of retaining wall design using evolutionary algorithms", Struct. Multidiscip. O., 55(3), 809-825. https:/doi.org/10.1007/s00158-016-1521-3.
  14. Gandomi, A.H., Kashani, A.R. and Zeighami, F. (2017), "Retaining wall optimization using interior search algorithm with different bound constraint handling", Int. J. Numer. Anal. Met. Geomech., 41, 1304-1331. https:/doi.org/10.1002/nag.2678.
  15. Ghazavi, M. and Bonab, S.B. (2011), "Optimization of reinforced concrete retaining walls using ant colony method", Proceedings of the 3rd International Symposium on Geotechnical Safety and Risk (ISGSR), Munich, Germany, June.
  16. Ghazavi, M. and Salavati, V. (2011). "Sensitivity analysis and design of reinforced concrete cantilever retaining walls using bacterial foraging optimization algorithm", Proceedings of the 3rd International Symposium on Geotechnical Safety and Risk (ISGSR), Munich, Germany, June.
  17. Kalemci, E.N. and Ikizler, S.B. (2020), "Rao-3 algorithm for the weight optimization of reinforced concrete cantilever retaining wall", Geomech. Eng., 20(6), 527-536. https:/doi.org/10.12989/gae.2020.20.6.527.
  18. Kalemci, E.N., Ikizler, S.B., Dede, T. and Angin, Z. (2020), "Design of reinforced concrete cantilever retaining wall using grey wolf optimization algorithm", Structures, 23, 245-253. https:/doi.org/10.1016/j.istruc.2019.09.013.
  19. Kaveh, A. and Abadi, A.S.M. (2011), "Harmony search based algorithms for the optimum cost design of reinforced concrete cantilever retaining walls", Int. J. Civ. Eng., 9(1), 1-8.
  20. Kaveh, A. and Behnam, A.F. (2013), "Charged system search algorithm for the optimum cost design of reinforced concrete cantilever retaining walls", Arab. J. Sci. Eng., 38(3), 563-570. https:/doi.org/10.1007/s13369-012-0332-0.
  21. Kaveh, A., Biabani Hamedani, K. and Zaerreza, A. (2020), "A set theoretical shuffled shepherd optimization algorithm for optimal design of cantilever retaining wall structures", Eng. Comput., 1-18. https:/doi.org/10.1007/s00366-020-00999-9.
  22. Kaveh, A. and Farhoudi, N. (2016), "Dolphin echolocation optimization for design of cantilever retaining walls", Asian J. Civ. Eng., 17(2), 193-211.
  23. Kaveh, A., Kalateh-Ahani, M. and Fahimi-Farzam, M. (2013), "Constructability optimal design of reinforced concrete retaining walls using a multi-objective genetic algorithm", Struct. Eng. Mech., 47(2), 227-245. https:/doi.org/10.12989/sem.2013.47.2.227.
  24. Kaveh, A. and Khayatazad, M. (2014), "Optimal design of cantilever retaining walls using ray optimization method", Iran. J. Sci. Technol. Trans. Civ. Eng., 38(C1), 261-274. https:/doi.org/10.22099/IJSTC.2014.1868.
  25. Kaveh, A. and Sabzi, O. (2012), "Optimal design of reinforced concrete frames using big bang-big crunch algorithm", Int. J. Civ. Eng., 10(3), 189-200.
  26. Kayhan, A.H. and Demir, A. (2016), "Optimum design of reinforced concrete cantilever retaining walls with particle swarm optimization", Pamukkale Univ. J. Eng. Sci., 22(3), 129-135. https:/doi.org/10.5505/pajes.2015.22590.
  27. Khajehzadeh, M., Taha, M.R. and Eslami, M. (2014), "Multiobjective optimisation of retaining walls using hybrid adaptive gravitational search algorithm", Civ. Eng. Environ. Syst., 31(3), 229-242. https:/doi.org/10.1080/10286608.2013.853746.
  28. Kramer, S.L. (1996), Geotechnical Earthquake Engineering, Pearson Education India.
  29. Mergos, P.E. and Mantoglou, F. (2019), "Optimum design of reinforced concrete retaining walls with the flower pollination algorithm", Struct. Multidiscip. O., 61(2), 575-585. https:/doi.org/10.1007/s00158-019-02380-x.
  30. Meyerhof, G.G. (1953), "The bearing capacity of foundations under eccentric and inclined Loads", Proceedings of the 3rd International Conference on Soil Mechanics and Foundation Engineering, Zurich, Switzerland, August.
  31. Mononobe, N. and Matsuo, H. (1929), "On determination of earth pressures during earthquakes", Proceedings of the World Engineering Congress, Tokyo, Japan.
  32. Nandha Kumar, V. and Suribabu, C.R. (2017), "Optimal design of cantilever retaining wall using differential evolution algorithm", Int. J. Optimiz. Civ. Eng., 7(3), 433-449.
  33. Okabe, S. (1924), "General theory on Earth pressure and seismic stability of retaining wall and dam", J. Japan Soc. Civ. Eng., 10(6), 1277-1323.
  34. Ozturk, H.T., Dede, T. and Turker, E. (2020), "Optimum design of reinforced concrete counterfort retaining walls using TLBO, Jaya algorithm", Structures, 25, 285-296. https:/doi.org/10.1016/j.istruc.2020.03.020.
  35. Pei, Y. and Xia, Y. (2012), "Design of reinforced cantilever retaining walls using heuristic optimization algorithms", Procedia Earth Planet. Sci., 5, 32-36. https:/doi.org/10.1016/j.proeps.2012.01.006.
  36. Perea, C., Alcala, J., Yepes, V., Gonzalez-Vidosa, F. and Hospitaler, A. (2008), "Design of reinforced concrete bridge frames by heuristic optimization", Adv. Eng. Softw., 39(8), 676-688. https:/doi.org/10.1016/j.advengsoft.2007.07.007.
  37. Pourbaba, M., Talatahari, S. and Sheikholeslami, R. (2013), "A chaotic imperialist competitive algorithm for optimum cost design of cantilever retaining walls", KSCE J. Civ. Eng., 17(5), 972-979. https:/doi.org/10.1007/s12205-013-0283-3.
  38. Rahbari, P., Ravichandran, N. and Juang, C.H. (2017a), "Robust geotechnical design of a retaining wall subjected to earthquake loads", Proceedings of the Geotechnical Frontiers 2017, Orlando, Florida, U.S.A., March.
  39. Rahbari, P., Ravichandran, N. and Juang, C.H. (2017b), "Seismic geotechnical robust design of cantilever retaining wall using response surface approach", J. GeoEng., 12(4), 147-156. https:/doi.org/10.6310/jog.2017.12(4).2.
  40. Rao, R.V. (2020), "Rao algorithms: Three metaphor-less simple algorithms for solving optimization problems", Int. J. Industr. Eng. Comput., 11(1), 107-130. https:/doi.org/10.5267/j.ijiec.2019.6.002.
  41. Rao, R.V., Savsani, V.J. and Vakharia, D.P. (2011), "Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems", Computer-Aided Des., 43(3), 303-315. https:/doi.org/10.1016/j.cad.2010.12.015.
  42. Rao, R.V. and Waghmare, G.G. (2016), "A new optimization algorithm for solving complex constrained design optimization problems", Eng. Optimiz., 9(1), 60-83.. https:/doi.org/10.1080/0305215x.2016.1164855.
  43. Saribas, A. and Erbatur, F. (1996), "Optimization and sensitivity of retaining structures", J. Geotech. Eng., 122(8), 649-656. https:/doi.org/10.1061/(asce)0733-9410(1996)122:8(649).
  44. Sheikholeslami, R., Khalili, B.G., Sadollah, A. and Kim, J.H. (2015), "Optimization of reinforced concrete retaining walls via hybrid firefly algorithm with upper bound strategy", KSCE J. Civ. Eng., 20(6), 2428-2438. https:/doi.org/10.1007/s12205-015-1163-9.
  45. Shukla, A.K., Pippal, S.K. and Chauhan, S.S. (2019), "An empirical evaluation of teaching-learning-based optimization, genetic algorithm and particle swarm optimization", Int. J. Comput. Appl., 1-15. https:/doi.org/10.1080/1206212X.2019.1686562.
  46. Shukla, A.K., Singh, P. and Vardhan, M. (2018), "An empirical study on multi-objective swarm algorithm for standard multi-objective benchmark problems", Proceedings of the 3rd International Conference on Internet of Things and Connected Technologies (ICIoTCT), Jaipur, India, March.
  47. Shukla, A.K., Singh, P. and Vardhan, M. (2018), "Neighbour teaching learning based optimization for global optimization problems", J. Intell. Fuzzy Syst., 34(3), 1583-1594. https:/doi.org/10.3233/JIFS-169453.
  48. Shukla, A.K., Singh, P. and Vardhan, M. (2020), "An adaptive inertia weight teaching-learning-based optimization algorithm and its applications", Appl. Math. Model., 77, 309-326. https:/doi.org/10.1016/j.apm.2019.07.046.
  49. Talatahari, S. and Sheikholeslami, R. (2014), "Optimum design of gravity and reinforced retaining walls using enhanced charged system search algorithm", KSCE J. Civ. Eng., 18(5), 1464-1469. https:/doi.org/10.1007/s12205-014-0406-5.
  50. Temur, R. and Bekdas, G. (2016), "Teaching learning-based optimization for design of cantilever retaining walls", Struct. Eng. Mech., 57(4), 763-783. https:/doi.org/10.12989/sem.2016.57.4.763.
  51. Yang, X.S. (2012), Flower Pollination Algorithm for Global Optimization, Springer Berlin Heidelberg, Germany.
  52. Yepes, V., Alcala, J., Perea, C. and Gonzalez-Vidosa, F. (2008), "A parametric study of optimum earth-retaining walls by simulated annealing", Eng. Struct., 30(3), 821-830. https:/doi.org/10.1016/j.engstruct.2007.05.023.
  53. Yepes, V., Marti, J.V. and Garcia, J. (2020), "Black hole algorithm for sustainable design of counterfort retaining walls", Sustainability, 12(7). https:/doi.org/10.3390/su12072767.