Topological design of structures using population-based optimization methods

In this article, a number of well-established population-based optimization methods i.e. genetic algorithms, simulated annealing and population-based incremental learning are briefly reviewed and compared in terms of their philosophical basis. The use of the optimization methods for topology optimization is demonstrated. The article also presents an efficient numerical technique to prevent checkerboard formation in topology design. A number of design test-cases are assigned to measure the performances of the population-based methods. The optimum solutions obtained using these methods are illustrated and compared. Advantages and disadvantages of the optimization methods are discussed. It is shown that, based upon the convergence rate and consistency measure, simulated annealing is the best technique for this type of structural design.