Abstract
In structural engineering, either structure safety or sustainable design of structure is an important parameter, which must be considered. On the other hand, the issue based on the creation of an optimum model toward any design in the structural engineering area becomes possible by fulfilling the mentioned design conditions. In this regard, in the present study, a reinforced concrete (RC) beam model with a T-shape cross-section was tried to optimize in the way of providing the minimum carbon dioxide (CO2) emission from the structural materials comprised of both concrete and steel. In this direction, optimization applications were provided according to different concrete grades in terms of compressive strength, besides that optimal cost levels were also obtained for all of the design combinations. While the optimization analyses were conducted to minimize CO2 emission, a well-known metaheuristic algorithm called as flower pollination algorithm (FPA) was benefited. Therefore, both optimization outcomes and statistical evaluations of them were presented concerning the eco-friendliest, sustainable, and also conveniently cost designs through decreasing one of the detrimental factors as CO2 emission.
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References
Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220(4598):671–680
Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of ICNN’95-International conference on neural networks. Perth-Australia, pp 1942–1948
Dorigo M, Di Caro G (1999) Ant colony optimization: a new meta-heuristic. In: Proceedings of the 1999 congress on evolutionary computation-CEC99 (Cat. No. 99TH8406). IEEE, Wahington DC-USA, pp 1470–1477
Krishnanand KN, Ghose D (2009) Detection of multiple source locations using a glowworm metaphor with applications to collective robotics. In: Proceedings 2005 IEEE Swarm intelligence symposiumm (SIS 2005). IEEE, California-USA, pp 84–91
Karaboga D (2005) An idea based on honey bee swarm for numerical optimization. Technical Report-tr06, Computer Engineering Department, Engineering Faculty, Erciyes University, Talas, Turkey, pp 1–10
Erol OK, Eksin I (2006) A new optimization method: big bang–big crunch. Adv Eng Softw 37(2):106–111
Mehrabian AR, Lucas C (2006) A novel numerical optimization algorithm inspired from weed colonization. Eco Inf 1(4):355–366
Yang XS (2010) Nature-inspired metaheuristic algorithms, 2nd edn. Luniver Press, United Kingdom
Yang XS, Deb S (2009) Cuckoo search via lévy flights. In: World congress on nature & biologically inspired computing (NABIC 2009). IEEE Publications, India, pp 210–214
Yang XS (2010) A new metaheuristic bat-inspired algorithm. In: Nature inspired cooperative strategies for optimization (NICSO 2010). Springer, Berlin, Heidelberg, pp 65–74
Yang XS (2012) Flower pollination algorithm for global optimization. In: International conference on unconventional computing and natural computation. Springer, Berlin, Heidelberg, pp 240–249
Hatamlou A (2013) Black hole: a new heuristic optimization approach for data clustering. Inf Sci 222:175–184
Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46–61
Kaveh A, Mahdavi VR (2014) Colliding bodies optimization: a novel meta-heuristic method. Comput Struct 139:18–27
Abedinia O, Amjady N, Ghasemi A (2014) A new metaheuristic algorithm based on shark smell optimization. Complexity 21(5):97–116
Kiran MS (2015) TSA: tree-seed algorithm for continuous optimization. Expert Syst Appl 42(19):6686–6698
Wedyan A, Whalley J, Narayanan A (2017) Hydrological cycle algorithm for continuous optimization problems. J Optim, 1–25
Mohammadi-Balani A, Nayeri MD, Azar A, Taghizadeh-Yazdi M (2020) Golden eagle optimizer: a nature-inspired metaheuristic algorithm. Comput Ind Eng 152:107050
Hashim FA, Hussain K, Houssein EH, Mabrouk MS, Al-Atabany W (2021) Archimedes optimization algorithm: a new metaheuristic algorithm for solving optimization problems. Appl Intell 51(3):1531–1551
Chou JS, Truong DN (2021) A novel metaheuristic optimizer inspired by behavior of jellyfish in ocean. Appl Math Comput 389:125535
Yucel M, Bekdas G, Nigdeli SM, Sevgen S (2018) Artificial neural network model for optimum design of tubular columns. Int J Theor Appl Mech 3:82–86
Kayabekir AE, Nigdeli SM (eds) (2020) Metaheuristic approaches for optimum design of reinforced concrete structures: emerging research and opportunities: emerging research and opportunities. IGI Global
Mergos PE, Mantoglou F (2020) Optimum design of reinforced concrete retaining walls with the flower pollination algorithm. Struct Multidiscip Optim 61(2):575–585
Mevada A, Patel V, Arekar V (2021) Cost optimization of cantilever retaining wall using flower pollination algorithm. Int J Adv Res Sci Commun Technol (IJARSCT) 6(1):915–930
Yücel M, Bekdaş G, Nigdeli SM, Kayabekir AE (2021) An artificial intelligence-based prediction model for optimum design variables of reinforced concrete retaining walls. Int J Geomech 21(12):04021244
Nigdeli SM, Bekdaş G (2019) Optimum design of multiple positioned tuned mass dampers for structures constrained with axial force capacity. Struct Design Tall Spec Build 28(5):e1593
Yucel M, Bekdaş G, Nigdeli SM, Sevgen S (2019) Estimation of optimum tuned mass damper parameters via machine learning. J Build Eng 26:100847
da Silva CAX, Taketa E, Koroishi EH, Lara-Molina FA, Faria AW, Lobato FS (2020) Determining the parameters of active modal control in a composite beam using multi-objective optimization flower pollination. J Vibr Eng Technol 8(2):307–317
TS500: Turkish Standard Requirements for Design and Construction of Reinforced Concrete Structures. Ankara-Turkey (2020)
Paya-Zaforteza I, Yepes V, Hospitaler A, Gonzalez-Vidosa F (2009) CO2-optimization of reinforced concrete frames by simulated annealing. Eng Struct 31(7):1501–1508
Yepes V, Gonzalez-Vidosa F, Alcala J, Villalba P (2012) CO2-optimization design of reinforced concrete retaining walls based on a VNS-threshold acceptance strategy. J Comput Civ Eng 26(3):378–386
Republic of Turkey Ministry of Environment and Urbanization, Directorate of Higher Technical Board, 2021 Construction and Installation Unit Prices. https://webdosya.csb.gov.tr/db/yfk/icerikler//bf2021-turkce-20210129113217.pdf. Last accessed 31 Oct 2021
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Yücel, M., Nigdeli, S.M., Bekdaş, G. (2022). Minimization of the CO2 Emission for Optimum Design of T-Shape Reinforced Concrete (RC) Beam. In: Kim, J.H., Deep, K., Geem, Z.W., Sadollah, A., Yadav, A. (eds) Proceedings of 7th International Conference on Harmony Search, Soft Computing and Applications. Lecture Notes on Data Engineering and Communications Technologies, vol 140. Springer, Singapore. https://doi.org/10.1007/978-981-19-2948-9_13
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