利用蚁群算法求解机械加工路径规划问题

Solving Machining Path Planning Problem by Ant Colony Algorithm

针对机械加工中孔群加工刀具路径规划问题,采用蚁群算法,通过多目标搜索和并行计算,快速从众多可行加工路线中找到一条最短路径作为刀具运动的轨迹,该路径可以最大限度的节省加工过程中的空行程时间,提高整体加工效率。采用控制变量法和正交试验法,结合算例,分析研究算法实现过程中需优化取值的蚂蚁的数量、信息素重要程度因子、启发函数重要程度因子、信息素挥发因子、总信息量等5个重要参数对于最优解质量的影响,探究其作用规律,为进一步提高算法优化结果和改进算法提供参考依据。

Aiming at the problem of tool path planning for hole group machining in mechanical processing,ant colony algorithm is used.Through multi-objective search and parallel computing,a shortest path is quickly found from many feasible machining routes as the trajectory of tool motion.The path can save the empty travel time in the machining process and improve the overall machining efficiency.By using the control variable method and orthogonal test method,combined with an example,the influence of five important parameters that need to be optimized in the process of algorithm implementation on the quality of the optimal solution is analyzed and studied,and the rule of action is explored,which provides a reference for further improving the algorithm optimization results and improving the algorithm.