One optimizing method for moments of inertia applied with improved adaptive Genetic Algorithm

In this paper, a new optimizing method for the moments of inertia of a mechanical structure was advanced. First, a new optimal model for the moments of inertia was advanced, which only involved with single objective and single variable, in order to reduce the calculating complexity of traditional multi-objective and multi-constrained optimizing model for the moments of inertia; Then, a new strategy for the probability selection of the crossover and mutation operation was improved to form the IAGA. The calculating results proved that, comparing to the Standard Genetic Algorithm (SGA), the IAGA improved in this paper had the advantage of converging faster, more powerfully searching, and less possible of falling into the local optimum. By that, the feasibility of the method advanced in this paper was demonstrated.