Multi-objective optimization of reinforced concrete frames using NSGA-II algorithm

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.

Keywords:

• NSGA-II
• multi-objective optimization
• moment resisting frame
• reinforced concrete
• weight
• displacement
• Pareto front

Additional information

Notes on contributors

Mehdi Babaei

Mehdi BABAEI is an Assistant Professor in the Department of Civil Engineering at the University of Zanjan. He received his PhD (2012) and Master’s (2003) degrees in Structural Engineering from the Iran University of Science and Technology after obtaining his Bachelor’s in Civil Engineering in 2000. During his PhD study, he visited the Oxford University as a research student as well as participated in a short program at the Massachusetts Institute of Technology in 2010. His research has focused on the optimal design of structures, tall buildings, spatial structures, structural systems and sustainable design.

Masoud Mollayi

Masoud MOLLAYI earned his MSc in Structural Engineering from the University of Zanjan in 2015, after receiving his Bachelor in Civil Engineering. His main interest is to study heuristic algorithms and to develop new algorithms for structural optimization.