Optimum cost design of reinforced concrete beams using genetic algorithms

Abstract EN

This paper presents the application of Genetic Algorithms for the optimum cost design of reinforced concrete beams based on ACI Standard specifications.

The produced optimum design satisfies the strength, serviceability, ductility, durability and other constraints related to good design and detailing practice.

While most of the approaches reported in the literature consider the steel reinforcement and the cross-sectional dimensions of the beam as the variables taking into account the flexural only, in this research the dimensions and reinforcing steel were introduced as a design variable, taking into account flexural, shear and torsion effects on the beam.

The constant parameters include the number of bays, span’s lengths, support conditions, loads, material properties and unit costs.

The forces, moments and deformations needed in the GA constraints will be found from analysis.

The beam dimensions are corrected to the nearest 25 mm and the areas of longitudinal and transverse steel obtained from the design are converted into a least weight detailing of steel reinforcements.

This is achieved by generating a database of reinforcement templates containing different available reinforcement bar diameters in a pre-specified pattern, satisfying the user specified bar rules and other bar spacing requirements.

The optimum design results are compared with those in the available literature, and the results are presented.

It is concluded that the proposed optimum design model yields rational, reliable, economic and practical designs.