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Abstract
In recent decades, the use of genetic algorithm (GA) for optimization of structures has been highly attractive in the study of concrete and steel structures aiming at weight optimization. However, it has been challenging for multi-objective optimization to determine the trade-off between objective functions and to obtain the Pareto-front for reinforced concrete (RC) and steel structures. Among different methods introduced for multi-objective optimization based on genetic algorithms, Non-Dominated Sorting Genetic Algorithm II (NSGA II) is one of the most popular algorithms. In this paper, multi-objective optimization of RC moment resisting frame structures considering two objective functions of cost and displacement are introduced and examined. Three design models are optimized using the NSGA-II algorithm. Evaluation of optimal solutions and the algorithm process are discussed in details. Sections of beams and columns are considered as design variables and the specifications of the American Concrete Institute (ACI) are employed as the design constraints. Pareto-fronts for the objective space have been obtained for RC frame models of four, eight and twelve floors. The results indicate smooth Pareto-fronts and prove the speed and accuracy of the method.
Highlights
Considering the fact that reinforced concrete (RC) structures compared to steel structures have more variety in materials, optimization of RC structures are more complex than steel structures
Multi-objective optimization of reinforced concrete frames using non-dominated sorting genetic algorithm (NSGA)-II algorithm gated under complex constraints (Gervytė, Jarmolajeva 2013)
Two objective functions, including the total structural cost and the maximum roof displacement, which are in conflict, are defined and applied for the bi-objective optimization of RC models
Summary
Considering the fact that reinforced concrete (RC) structures compared to steel structures have more variety in materials, optimization of RC structures are more complex than steel structures. In 2003, the article of Camp et al (2003) was published about optimization of moment resisting frames using genetic algorithms. Multi-objective optimization of reinforced concrete frames using NSGA-II algorithm gated under complex constraints (Gervytė, Jarmolajeva 2013). The powerful algorithms of NSGA have been used for the optimization in various fields including RC structures Some of these studies are: two-objective optimization of CO2emissions and cost for composite building design using NSGA (Park et al 2012), synthesis of truss structure designs by NSGA-II and Node Sort algorithm (Stanković et al 2012), and cost and CO2 emission optimization of steel reinforced concrete columns in high-rise buildings (Park et al 2013).
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