Improved Genetic Algorithm of Multi-objective Structure Fuzzy Optimization

A kind of improved symmetry and a kind of improved asymmetry genetic algorithm were introduced to solve the general multi-objective optimization problem according to the different important degree of objective functions and constraint functions. It can search the optimum solution from many initial points at the same time. The example of helical gear was given to demonstrate these algorithms. By applying Matlab toolbox we obtained the optimal values of various multi-objective optimization fuzzy models. The results showed that the improved algorithm has fast convergence speed of the solution process and high accuracy, and can obtain the global optimum solution of the whole optimization problems comparing with the traditional multi-objective optimization, and it also meets the security, economical efficiency and other requirements.