面轨道特征的矩形排样与加工路径优化方法研究

Research on Packing Problem and Cutting Path Optimization of Rectangle with Surface Orbit Characteristics

为了解决实际生产中遇到的一种带有面轨道特征的矩形排样问题,重点研究了自适应遗传算法和图论相结合的优化方法,极大提高了切削加工效率。该方法将路径优化问题转化为一个考察无向图连通性问题,并利用遗传算法在解空间中进行全局搜索,以寻找加工路径最优解,并按照BL定位策略完成对矩形的排样。通过对遗传算法的改进:(1)对初始个体基因位的合法性判断,并利用深度优先遍历结果评估个体性能的优劣;(2)交叉、变异算子均采用自适应机制,并且执行变异操作的对象限定为一条染色体上的断点集,极大提高了算法的性能。最后,通过实验验证了该算法在绝大多数情况下完全可以找到满足需求目标的结果,是一种非常可靠的方法。

The purpose of this paper is to solve the equilateral rectangular packing problem characterized by surface orbit arised in practical production.We focus on the optimization system based on adaptive genetic algorithm and graph theory,and greatly improve the cutting efficiency.Our method target the optimization of the machining path,in this method,the path optimization problem is turned into an undirected graph connectivity problem,and using genetic algorithm to find the optimized machining path.The optimal solution of the final search is used to arrange the rectangular parts according to BL positioning strategy.Through the improvement of genetic algorithm,such as:①the judgment of the legitimacy of the initial individual genes,and using the depth first traversal results evaluation of individual performance.②The crossover and mutation operators use adaptive mechanism,and the object that performs the mutation operation is limited to a broken point set on a chromosome,which greatly improves the performance of the algorithm.Finally,the experiments show that the algorithm can provide the available solution in most cases,and it is also a very reliable method.