Cost optimization of reinforced concrete frames using genetic algorithms

Abstract

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