融合帝国竞争与遗传算法的零件加工工艺排序方法

A part machining process ranking method incorporating imperial competition and genetic algorithm

  • 摘要: 针对计算机辅助工艺规划中的零件加工工艺排序问题,以最小化机床、装夹以及刀具变更次数为优化目标,构建了工艺排序的数学模型,并提出了融合帝国竞争与遗传算法的优化求解方法,将帝国竞争算法输出的较优加工序列作为遗传算法的初始种群,通过融合帝国竞争算法不受初始种群影响的特性和遗传算法的快速收敛能力提升算法求解性能。实验结果表明:混合算法寻找最优解的效果比采用单一算法的效果更好,并且收敛速度更快。

     

    Abstract: Aiming at the problem of part machining process ordering in computer-aided process planning, with the optimization goal of minimizing the number of machine tools, clamping, and tool changes, a mathematical model of process order was constructed, and an optimization solution method integrating imperial competition and the genetic algorithm was proposed. The optimal processing sequence output by the imperial competition algorithm is used as the initial population of the genetic algorithm, and the solving performance of the algorithm is improved by integrating the characteristics of the imperial competition algorithm that are not affected by the initial population and the rapid convergence ability of the genetic algorithm. The experimental results show that the effect of the hybrid algorithm to find the optimal solution is better than that of the single algorithm, and the convergence speed is faster.

     

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