Multi-objective optimization of reinforced concrete frames using NSGA-II algorithm. Issue 4 (1st October 2016)

• Record Type: Journal Article
• Authors: Babaei, Mehdi; Mollayi, Masoud
• Is Part Of: Engineering structures and technologies. Volume 8:Issue 4(2016)
• Page Start: 157
• Page End: 164
• Publication Date: 2016-10-01
• Subjects: NSGA-II -- multi-objective optimization -- moment resisting frame -- reinforced concrete -- weight -- displacement -- Pareto front; Structural engineering -- Periodicals; Structural engineering -- Research -- Periodicals; 624.105
• DOI: 10.3846/2029882X.2016.1250230
• Languages: English
• ISSNs: 2029-882X

Abstract

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.