Optimal design of reinforced concrete beams using genetic algorithms

Abstract

This paper presents a method for optimizing the design of reinforced concrete beams subject to a specified set of constraints. A new model of optimization is proposed, leading to more realistic and practical designs. As there are an infinite number of possible beam dimensions and reinforcement ratios that yield the same moment of resistance, it becomes difficult to achieve the least-cost design by conventional iterative methods. We present a method based upon a search technique using genetic algorithms. Several applications show how our system provides more realistic designs than other methods based on mathematical programming techniques. Also, we show our results of experimenting with several representation schemes for the genetic algorithm, and the methodology that we used to adjust its parameters — i.e. population size, crossover and mutation rates and maximum number of generations—so that it produces a reasonable answer in a short period of time. A prototype of this system is currently being tested at our school, to see its potential use as a tool for real-world applications.