Optimum cost design of reinforced concrete continuous beams using Genetic Algorithms

Abstract

This paper presents the application of genetic algorithms (GA) for the optimum cost design of reinforced concrete continuous beams based on the standard specifications of the American Concrete Institute. 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 steel reinforcement and cross-sectional dimensions of beam as design variables of the flexural aspect only, the dimensions and reinforcing steel in this research were introduced as design variables, considering the flexural, shear, and torsion effects on the beam. The constant parameters specified prior to the solution of the optimization problem included the number of bays, lengths of span, support conditions, loads, material properties, and unit costs. The forces, moments, and deformations needed in the GA constraints were determined from the analysis. The beam dimensions were corrected to the nearest 25 mm, and the areas of the longitudinal and transverse steel obtained from the design were converted into the least weight detailing of steel reinforcements. This conversion was 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 were compared with those in the available literature. Upon the illustration of an example problem and the presentation of results, the proposed optimum design model is concluded to yield rational, reliable, economic, and practical designs.