改进蚁群算法在并联六自由度平台优化设计中的应用

蚁群算法在解决组合优化问题上有着良好的适应性，但直接应用于求解连续优化问题难以获得理想的效果．通过对蚁群算法中的全局搜索、局部搜索以及信息素更新规则等环节进行有效的改进，构成了可用于连续优化问题求解的改进蚁群算法．将该算法应用于以灵巧度为目标函数的并联六自由度平台结构设计问题中，通过与采用基本蚁群算法得到的优化结果进行比较，证实了改进蚁群算法具有较好的全局优化能力和较快的收敛速度，可以有效求解并联六自由度平台结构设计这一类连续优化问题．

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.