Comparative Study on Recent Metaheuristic Algorithms in Design Optimization of Cold-Formed Steel Structures

Abstract

Sustainable construction aims at reducing the environmental impact of buildings on human health and natural environment by efficiently using energy, resources and reducing waste and pollution. Building construction has the capacity to make a major contribution to a more sustainable future of our World because this industry is one of the largest contributors to global warming. The use of coldformed steel framing in construction industry provides sustainable construction which requires less material to carry the same load compare to other materials and reduces amount of waste mimum design algorithms are developed for cold-formed steel frames made of thin-walled sections using the recent metaheuristic techniques. The algorithms considered are firefly, cuckoo search, artificial bee colony with levy flight, biogeography-based optimization and teaching-learning-based optimization algorithms. The design algorithms select the cold-formed thin-walled C-sections listed in AISI-LRFD (American Iron and Steel Institution, Load and Resistance Factor Design) in such a way that the design constraints specified by the code are satisfied and the weight of the steel frame is the minimum. A real size cold-formed steel building is optimized by using each of these algorithms and their performance in attaining the optimum designs is compared.

Utilization of Harmony Search Algorithm in Optimal Structural Design of Cold-Formed Steel Structures

“…Two-storey, 1211-member lightweight cold-formed steel frame shown in Fig. 2 is selected as design problem [15]. 3-D, plan and floor views of the frame are shown in the same figure respectively.…”

Estimation of rigidity of concrete based on multi parameters using artificial bee colony optimization method with levy flight distribution

“…ABC method is one of the well-known meta-heuristic optimization method developed by Karaboga and Basturk [13][14][15]. Researchers used the ABC method in many engineering fields such as electric power systems [16], air vehicle path planning [17], the design of civil engineering structures [18][19][20][21][22][23][24][25]. The ABC method is also used to solve regression models such as symbolic regression [26], support vector regression system [27,28], stepwise regression -correlation [29].…”

Cost optimization of reinforced concrete cantilever retaining walls under seismic loading using a biogeography-based optimization algorithm with Levy flights

“…In the literature, there are many available successful applications of metaheuristic algorithms on structural optimization problems such as pin joint structures (Dogan, Hasancebi, and Saka 2009;Hasançebi et al 2009;Hasancebi and Azad 2015), steel rigid frames (Hasançebi, Erdal, and Saka 2010;Hasançebi et al 2011;Azad, Hasancebi, and Azad 2013;Saka and Geem 2013;Azad and Hasancebi 2015), skeletal structures (Saka 2014), semi-rigid frames (Artar and Daloglu 2015b), composite steel frames (Artar and Daloglu 2015a), RC frames (Akin and Saka 2015) and retaining walls (Akin and Saka 2010; Camp and Akin 2012). Furthermore, review studies are found in the literature on the applications of metaheuristic algorithms Saka and Geem 2013;Sahab, Toropov, and Gandomi 2013;Zavala et al 2014;Degertekin and Geem 2016;Saka, Hasançebi, and Geem 2016;Yang, Bekdaş, and Nigdeli 2016).…”

“…The BBO algorithm was first developed by Simon (2008), who adopted the theory of island biogeography. Since its emergence, the BBO algorithm has been applied to many engineering design optimization problems, such as truss structures (Jalill, Hosseinzadeh, and Kaveh 2014), soft-sensor models (Wang et al 2015), AC transmission system devices (Roy, Ghoshal, and Thakur 2011), steel frames (Çarbaş 2016) and cold-formed structures (Saka et al 2015). However, its application to the optimum design of the RC cantilever retaining wall problem is not found in the current literature, other than a conference study which is related to the optimum carbon dioxide emissions of the RC retaining wall design (Aydogdu and Akin 2015).…”