Research Article
Optimum design of cold-formed thin-walled sections subjected to axial and bi-axial bending using artificial bee colony algorithm
Serdar Carbas*1, Mehmet Polat Saka2
1Department of Civil Engineering, Karamanoglu Mehmetbey University, Karaman, Turkey
2Department of Civil Engineering, University of Bahrain, Isa-Town, Bahrain
Keywords
Abstract
Structural optimization,
Discrete optimization,
Artificial bee colony algorithm,
Metaheuristic techniques,
Cold-formed thin-walled open sections
Sustainable development in construction industry is emerging as a major issue among cities and communities in the current century. As global climate change becomes an increasingly serious concern for the future and construction industry dependence on fossil fuels for energy creates greater adverse influence on human health and natural environment, an interest in high-efficient, low environmental impact buildings has begun to transform the notion of building design, construction, and operation. As it stands, the most of the standard buildings in the world consume an extraordinary amount of resources while taking an enormous toll on the environment. The utilization of cold-formed thin-walled open steel sections in structural sites supplies green structural opportunities demanding less material and cost while providing high strength. The developed algorithm for this study obtains the optimum geometric dimensions of cold-formed thin-walled open steel sections under various external loading. Moreover, this design algorithm takes into account of the effect of geometric nonlinearity as well as effect of warping. Also the displacement and stress constraints are included in the formulation of the design problem. The optimum design problem obtained turn out to be mixed integer and discrete programming problem. Artificial Bee Colony (ABC) algorithm is used to obtain its solution. This technique is a recent numerical optimization technique which mimics the intelligent behavior of honey bee swarm. The recent studies with the ABC method have shown its effectiveness and robustness in finding the optimum solution of combinatorial optimization problems. A design example is included to demonstrate the efficiency of the optimum design algorithm developed.
© 2015 MIM Research Group. All rights reserved.