Optimization of 3d trusses with adaptive approach in genetic algorithms

This paper discusses the adaptive approach in genetic algorithms (GAs). It is tried to show how the adaptive approach affects the performance of GAs, suggesting some improvements in both the penalty function, and mutation and crossover. A strategy is also considered for member grouping to reduce the size of the problem. Some practical design of space truss examples taken from technical literature are optimized by the algorithm suggested in the current work. Design constraints such as displacement, tensile stress and stability given by national specifications are incorporated and the results are compared with the ones obtained by previous studies. It is concluded that the member grouping together with the adaptive approach increase the probability of catching the global solution and enhance the performance of GAs.