Application of an improved ant colony algorithm to optimal design of the parallel 6-DOF platform

The ant colony algorithm has good adaptability when solving combined optimization problems, it isn't very good for continuous optimization problems. By improving global searching, local searching and the pheromone updating rule, a novel ant colony algorithm was developed for solving the continuous optimization problem. Then this method was applied to the structural design of a parallel six degrees of freedom platform, in which dexterity of motion was considered as the objective function. Comparing results obtained from the improved algorithm with the standard algorithm, the new method is better at global optimization and has a faster convergence rate, thus it can be used to efficiently solve continuous optimization problems such as the structural design of parallel six degrees of freedom platforms.