مهندسی سازه و ساخت

مهندسی سازه و ساخت

Optimizing Reinforced Concrete Cantilever Retaining Walls Using Artificial Bee Colony Algorithm

نوع مقاله : علمی - پژوهشی

نویسندگان
1 استادیار، دانشکده فنی و مهندسی، دانشگاه بین المللی اهل بیت (ع)، تهران، ایران
2 دانشکده مهندسی عمران، دانشگاه علم و فرهنگ، تهران، ایران
3 استادیار، دانشکده فنی و مهندسی، دانشگاه بین المللی اهل بیت (ع) تهران، ایران
چکیده
The Artificial Bee Colony (ABC) Algorithm is a sophisticated optimization technique that is inspired by the intelligent behaviors of honey bee swarms. These behaviors, such as foraging and communication within complex social structures, serve as the foundation for the algorithm's effectiveness. In this paper, the ABC algorithm is utilized to optimize the design of reinforced cantilever concrete retaining walls, with the goal of minimizing both cost and weight. The results are compared to existing literature, demonstrating the success of the ABC algorithm in achieving the objectives. Furthermore, a comparison is conducted between the optimized design and a conventional manual design, revealing a significant reduction in cost and weight through optimization. Additionally, two types of reinforced concrete cantilever retaining walls-a T-shape wall with variable stem thickness and a standard T-shape wall-are presented and compared, considering their differing variables and constraints. These comparisons are made for two objective functions: the cost and weight of the wall. To further investigate the impact of initial parameters, such as the unit weight of soil and stem height, a sensitivity analysis is conducted. The robustness of the ABC algorithm in optimizing the cost and weight of reinforced concrete cantilever retaining walls is demonstrated by the results.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Optimizing Reinforced Concrete Cantilever Retaining Walls Using Artificial Bee Colony Algorithm

نویسندگان English

Mehdi Shalchi Tousi 1
Samane Laali 2
Payam Tarighi 3
1 Assistant Professor Faculty of Technology and Engineering, Ahlul Bayt International University, Tehran, Iran.
2 Department of Civil Engineering, University of Science and Culture, Tehran, Iran.
3 Assistant Professor, Department of Civil Engineering, Faculty of Technology and Engineering, Ahlul Bayt International University, Tehran, Iran.
چکیده English

The Artificial Bee Colony (ABC) Algorithm is a sophisticated optimization technique that is inspired by the intelligent behaviors of honey bee swarms. These behaviors, such as foraging and communication within complex social structures, serve as the foundation for the algorithm's effectiveness. In this paper, the ABC algorithm is utilized to optimize the design of reinforced cantilever concrete retaining walls, with the goal of minimizing both cost and weight. The results are compared to existing literature, demonstrating the success of the ABC algorithm in achieving the objectives. Furthermore, a comparison is conducted between the optimized design and a conventional manual design, revealing a significant reduction in cost and weight through optimization. Additionally, two types of reinforced concrete cantilever retaining walls-a T-shape wall with variable stem thickness and a standard T-shape wall-are presented and compared, considering their differing variables and constraints. These comparisons are made for two objective functions: the cost and weight of the wall. To further investigate the impact of initial parameters, such as the unit weight of soil and stem height, a sensitivity analysis is conducted. The robustness of the ABC algorithm in optimizing the cost and weight of reinforced concrete cantilever retaining walls is demonstrated by the results.

کلیدواژه‌ها English

Retaining wall
Bee Colony Algorithm
Optimization
Wall cost and weight
T-shape walls
[1]    Saribas, A., Erbatur, F. (1996). “Optimization and sensitivity of retaining structures”, Journal of Geotechnical Engineering, 122(8), 649-656. https://doi.org/10.1061/(ASCE)0733-9410(1996)122:8(649)
[2]    Ceranic, B., Fryer, B. and Baines, R.W. (2001). “An application of simulated annealing to the optimum design of reinforced concrete retaining structures”. Computers and Structures, 79, 1569-1581. https://doi.org/10.1016/S0045-7949(01)00037-2
[3]    Sivakumar, G. L. and Munwar, B. (2008). “Optimum design of cantilever retaining walls using target reliability approach”. International Journal of Geomechanics, 8(4), 240-252. https://doi.org/10.1061/(ASCE)1532-3641(2008)8:4(240)
[4]    Yepes, V., Alcala, J., Perea, C., Gonzalez-Vidosa, F. (2008). “A parametric study of optimum earth retaining walls by simulated annealing”. Engineering Structures, 30(3), 821-830. https://doi.org/10.1016/j.engstruct.2007.05.023
[5]    Ghazavi, M., Bazzazian Bonab, S. (2011). “Learning from ant society in optimizing concrete retaining walls”. Journal of Technology & Education, 5(3), 234-241. https://doi.org/10.22061/tej.2011.285
[6]      Ghazavi, M. and Salavati, V. (2011). “Sensitivity analysis and design of reinforced concrete cantilever retaining walls using bacterial foraging optimization algorithm”. Bundesanstalt für Wasserbau ISBN 978-3-939230-01-4.
[7]    Kaveh, A. and Behnam, A. F. (2013). Charged system search algorithm for the optimum cost design of reinforced concrete cantilever retaining wall. Arabian Journal of Science and Engineering, 38, 563–570. https://doi.org/10.1007/s13369-012-0332-0
[8]    Karaboga, D. and Basturk, B. (2008). “On the performance of artificial bee colony (ABC) algorithm”. Applied Soft computing, 8, 687-697. https://doi.org/10.1016/j.asoc.2007.05.007
[9]    Shalchi Tousi, M., Laali, S., Ghazavi, M. (2022), “Optimization of reinforced concrete cantilever retaining walls by the use of intelligent water drops algorithm (IWDA)”, International Journal of Advanced Structural Engineering, 12(3), 619–624. https://doi.org/10.1007/ijase.2023.1971683.1059
[10] Shalchi Tousi, M., Laali, S. (2022). “Optimum Design of Reinforced Concrete Cantilever Retaining Walls by Cuckoo Optimization Algorithm (COA)”, International Journal of Advanced Structural Engineering, 12(4), 645–662. https://doi.org/10.1007/ijase.2023.1971723.1060
[11]  Shalchi Tousi , M., Ghazavi, M.,  Laali, S. (2021). “Optimizing Reinforced Concrete Cantilever Retaining Walls Using Gases Brownian Motion Algorithm (GBMOA)”, Journal of Soft Computing in Civil Engineering, 5(1), 1-18. https://doi.org/10.22115/scce.2021.248638.1256
[12] Kalmeci, E.N., Ikizler, S.B., Dede, T., Angin, Z. (2020), “Design of reinforced concrete cantilever retaining wall using Grey wolf optimization algorithm”, Structures, 23, 245-253.
[13] Romani, J., Ossandón, D., Sepúlveda, R., Astudillo, N., Yepes, V. (2023), “Optimizing Retaining Walls through Reinforcement Learning Approaches and Metaheuristic Techniques”, Mathematics, 11, 2104. https://doi.org/10.3390/math11092104
[14]  Keivanian, F., Chiong, R., Kashani, A. and Gandomi, A. (2023), “A fuzzy adaptive metaheuristic algorithm for identifying sustainable, economical, and earthquake-resistant reinforced concrete cantilever retaining walls”, Journal of Computational Science, 70, 101978. https://doi.org/10.1016/j.jocs.2023.101978
[15]  Tayfur, B., KAMILOĞLU, H. (2024), “Optimization of Cantilever Retaining Wall Design Using Improved Teaching-Learning-Based Optimization Algorithms”, Journal of Experimental and Computational Engineering, 3(2), 134-150. https://doi.org/10.62520/fujece.1430236
[16]  Shenouda, M. and Ali, M. (2024), “Simulation-Optimization Model for the Structural Design of Cantilever Retaining walls”, Asian Journal of Civil Engineering, 17. https://doi.org/10.1007/s42107-024-01028-6
[17] Boukhatem, G., Moufida, M., Kamel, G., Bekkouche Souhila, R. (2023), “Mono-objective Optimization of Retaining Wall Using Genetic Algorithm”, Journal of Civil Eng., 18(1). https://doi.org/10.2478/sspjce-2023-0012
[18] Khajehzadeh, M., Taha, M.R., El-Shafie, A. et al. (2011). "Modified particle swarm optimization for optimum design of spread footing and retaining wall", J. Zhejiang Univ. Sci., 12, 415–427. https://doi.org/10.1631/jzus.A1000252
[19] Camp, Ch., Akin, A. (2012). "Design of Retaining Walls Using Big Bang–Big Crunch Optimization", Journal of Structural Engineering, 138(3), https://doi.org/10.1061/(ASCE)ST.1943-541X.0000461
[20] Kashani, A.R., Gandomi, A.H., Azizi, K. et al. (2022), "Multi-objective optimization of reinforced concrete cantilever retaining wall: a comparative study", Struct Multidisc Optim, 65(262). https://doi.org/10.1007/s00158-022-03318-6
[21] Gandomi, A.H., Kashani, A.R., Roke, D.A. et al. (2017). "Optimization of retaining wall design using evolutionary algorithms", Struct Multidisc Optim, 55, 809–825. https://doi.org/10.1007/s00158-016-1521-3
[22] Ibrahim Aydogdu (2016), "Cost optimization of reinforced concrete cantilever retaining walls under seismic loading using a biogeography-based optimization algorithm with Levy flights", Engineering Optimization. http://dx.doi.org/10.1080/0305215X.2016.1191837
[23] Molina-Moreno, F., Garsia-Segura, T., Marti, J., Yepes, V. (2017), " Optimization of buttressed earth-retaining walls using hybrid harmony search algorithms", Engineering Structures, 134, 205-216. http://dx.doi.org/10.1016/j.engstruct.2016.12.042
[24] Temur, Rasim, and Gebrail Bekdaş. (2016), "Teaching Learning-Based Optimization for Design of Cantilever Retaining Walls", Structural Engineering and Mechanics, 57(4), 763-783. https://doi.org/10.12989/sem.2016.57.4.763.
[25] Karaboga, D. and Ozturk, C. (2011). “A novel clustering approach: artificial bee colony (ABC) algorithm”. Applied Soft computing, 11(1), 652-657. https://doi.org/10.1016/j.asoc.2009.12.025
[26] Karaboga, D., (2005). "An idea based on honey bee swarm for numerical optimization", Tech. rep., technical report-tr06, Erciyes University, Engineering Faculty, Computer Engineering Department.
[27]    Shah, Habib & Tairan, Nasser & Mashwani, Wali & Alsewari, AbdulRahman & Jan, Muhammad Asif & Badshah, Gran. (2017). "Hybrid Global Crossover Bees Algorithm for Solving Boolean Function Classification Task", Conference Paper in Lecture Notes in Computer Science.
[28]    ACI 318-08, (2008). “Building code requirements for structural concrete and commentary”. American Concrete Institute International.
[29]    Bowles, J., (1992). “Foundation analysis and design”. 6th edition, McGraw-Hill, New York.

  • تاریخ دریافت 18 دی 1403
  • تاریخ بازنگری 25 فروردین 1404
  • تاریخ پذیرش 16 اردیبهشت 1404