Effect of mutation schemes on convergence to optimum design of steel frames

In this paper an attempt is made to modify a distributed genetic algorithm (DGA) to minimize the weight of steel frames. The main aspects of modifications include the twin analogy and a number of mutation schemes. Although the mutation is a secondary operator in the GA, it plays an influential role in diversifying the population and exploring more feasible design space. In this research, four different mutation schemes are examined and their effects on convergence to optimum solutions are evaluated. Using three benchmark examples, it is demonstrated that mutation operator can efficiently influence on the speed of convergence and consequently saving computation time. As coding a program is required, the DO-DGA software has been developed to handle the algorithm. DO-DGA applies modified DGA, including different mutation schemes, to obtain the global optimum solution.