Genetic Algorithms in Discrete Optimization of Steel Truss Roofs

Abstract

Genetic algorithms have their basis in Darwin's theory of survival of the fittest. These algorithms have been used successfully in genetics and recently in a variety of optimization problems. In this paper, the mixed layout and sizing optimization problem of a typical steel roof is solved using a genetic algorithm for the layout part, and a logic program is used for the sizing optimization of the truss roof. The method is applied to large‐design‐space problems, and near‐optimum solutions are found in reasonable computing time. The genetic algorithm is based on a roulette‐wheel reproduction scheme, a single point crossover, and a standard mutation scheme. An elitist strategy is also used that passes the best designs of a generation to the next generation. Numerical results are presented that show the efficiency of the method. Estimates of the various parameters of the algorithm are determined, which render the method an efficient optimization method for discrete structural design problems.