Cost optimization of reinforced concrete frames using genetic algorithms

Abstract

Cost optimization of reinforced concrete building frames using genetic algorithms is presented. Unlike previous works that used simplified discrete or continuous optimization models, this work considers constructability issues as well as the effects of shear and torsional actions in the design optimization of reinforced concrete frames. An integrated software system has been developed to implement the proposed optimization procedure using genetic algorithms. Examples have been incorporated in order to compare the results from the proposed study with that of a previous work which follows a different heuristic and with the traditional “design–check–revise” method. The structural design procedures recommended in the Eurocode-2 have been strictly followed in this work. Special emphasis has been given to structural analysis methods and studying computational efficiency of the developed framework. To improve the performance and computational complexity of the algorithm, the effect of genetic parameters such as mutation and crossover on the optimization process has been thoroughly studied. The method developed in this work proves to have a lot of advantages over the traditional “design–check–revise” paradigm and other heuristic methods.