On the performance of a modified multiple-deme genetic algorithm in LRFD design of steel frames

This paper investigates the performance of a multiple-deme genetic algorithm (GA) with modified reproduction operators, in optimal design of planar steel frames according to the AISC-LRFD specification. The design objective is to minimise the weight of frame subject to strength, displacement and constructability constraints. A number of new crossover and mutation operators, used alongside the standard operators are utilised in optimum design of a number of steel frames subjected to the constraints of the AISC-LRFD specification, with and without considering the second order effects, as set out by the code requirements. This modified GA (MGA) is shown to have a very fast convergence and to produce relatively high-quality designs. This paper also utilizes the concept of multiple-deme in the GA, as it has been used successfully for other metaheuristic population-based methods. The multiple-deme GA is used alongside the modified GA operators and the algorithm is named the modified multiple-deme GA (MMDGA). The modified GA (MGA) and modified multiple-deme GA (MMDGA) are applied to three benchmark problems and the results are compared to those obtained by other metaheuristic methods. In the majority of cases, the results of comparisons suggest the superiority of the MMDGA in terms of the quality of final design and the total number of performed finite elements analyses.