Choosing Methods for Manufacture of Reinforced Concrete Frames Based on Solution of Optimisation Problems

  • Igor SerpikEmail author
  • Inna Mironenko
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1116)


A methodology has been suggested for assessing the economic efficiency of making decisions on the selection of a technology for constructing plane reinforced concrete frames manufactured without pre-stressing reinforcement. The approach is based on execution of the optimum synthesis of a structure for each of the process options in question. The optimisation is carried out using a metaheuristic scheme of evolutionary modelling. A task has been set to minimise the planned manufacturing cost of a reinforced-concrete frame while taking into consideration the peculiarities of the processes for cast-in-situ, prefabricated, and composite structures. The regulatory limitations in terms of strength, stiffness, and crack resistance of the framework are taken into consideration. Concrete and reinforcing steel classes, cross-section values of columns and cross bars, as well as the amount and diameters of reinforcement bars vary on discrete sets. The search is performed using a genetic algorithm stipulating functioning of the main and elite populations. In the main population, individuals are subjected to single-point crossover, mixed mutation execution procedures, and selection based on the criterion of minimum cost. The elite population is used for storage of efficient genetic material and replacement of inoperative individuals of the main population. When calculating the stress strain behaviour of the structure variants, the factors taken into consideration are the physically non-linear behaviour of concrete and reinforcement, and the possibility of formation of transverse cracks in concrete. The operability of the suggested methodology is illustrated via the example of selecting a method of constructing a double-span reinforced concrete frame.


Reinforced concrete frames Manufacturing process Cost Optimisation Evolutionary modelling 



The reported study was funded by RFBR according to the research project No. 18-08-00567.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Bryansk State Engineering Technological UniversityBryanskRussia

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