基于贪心-遗传算法的混合轨迹加工走刀空行程路径优化

Optimization Empty Run for Multiple Contour Mixed Path Processing Based on Greedy and Genetic Algorithm

针对数控自动编程中交互式图形文件存储图元的无序性,提出基于贪心算法和遗传算法的新型多轮廓混合轨迹加工路径优化方法,利用遗传算法对各个轮廓轨迹的前后加工顺序进行优化排序,并融合贪心算法对某种加工顺序中相邻轨迹段之间的空行路径的控制点进行选择,进而计算总空行程和个体的适应度,然后对个体进行评价选择、交叉、变异等遗传操作。该算法不仅简化了遗传算法的编码方式,而且还排除了无效解。经编程仿真及试验测试,结果表明:算法有效地缩短了刀具的空行程、减少了刀具的起落次数、提高了加工效率。

Aiming at the randomness of pel storage in the interactive graphics file used in the numerical control （NC） automatic programming, a new optimization method of contour machining path based on the greedy algorithm and genetic algorithm is proposed. The genetic algorithm is used to optimize the scheduling and processing sequence for each contour trajectory, and the greedy algorithm is also fused to select the control point of the empty run path between the two interfacing trajectories in the confirmed sequence. Then the total distance of empty run paths and the individual fitness are calculated according to the selected control points. The genetic manipulation is made to evaluate individual, which consists of selection, crossover and mutation. The method not only simplifies the coding, but also eliminates the invalid solution. The results of simulation and test prove that the method shortens the empty run distances, decreases the number of cutter landing gear, and improves the NC machining efficiency.