锻压技术

多变量编码遗传算法在管道类零件展开图排样中的应用

英文标题：Application of multivariate coding genetic algorithm in expanded layout for ventilation duct parts

作者：张京京龙华陈晓鹏陈年华

分类号：TP3-05

出版年,卷(期):页码：2022,47(11):146-150

摘要：

针对不规则通风管道展开件在排样中存在的材料利用率低、排样效率低、展开件形状难以表征等问题，在基本遗传算法的基础上提出了采用多变量编码遗传算法对展开件进行排样布局。该算法对零件排列次序、镜像参数、旋转角度和零件中心位置存储参数等多个变量采用十进制编码方法，随机生成初始种群，进行选择、交叉、变异操作，最终获得了展开件排样效果图。对比基本遗传算法与多变量编码遗传算法的排样效果可知，多变量编码遗传算法能够准确地表征排样件的几何形状及位置特征，保证了高效率排样，提高了排样的材料利用率，同时，验证了多变量编码遗传算法具有可行性与有效性，对于优化钣金件制造加工工艺、提高生产效率具有重要指导意义。

For the problems of low utilization rate of material, low efficiency of layout and difficult to characterize the shape of expanded part in the expanded layout of irregular ventilation duct parts, the layout of expanded part was proposed by a multivariate coding genetic algorithm based on the basic genetic algorithm. In this algorithm, many variables such as sort order of parts, mirror parameters, rotation angle and storage parameters of part center position were coded by decimal system, the initial population was randomly generated, and the selection, crossover and mutation operations were carried out. Finally, the layout effect diagram of expanded part was obtained. By comparing the layout effect of basic genetic algorithm and multivariate coding genetic algorithm, it can be seen that the multivariate coding genetic algorithm can accurately characterize the geometric shapes and positional features of layout parts, ensure the high efficiency of layout, and improve the material utilization rate of layout. At the same time, the feasibility and effectiveness of the multivariate coding genetic algorithm is verified, which has important guiding significance for optimizing the manufacturing process and improving the production efficiency of sheet metal parts.

基金项目：

湖南省教育厅科学研究项目（19C0623）

作者简介：张京京（1987-），女，硕士，讲师，E-mail：940112291@qq.com；通信作者：陈晓鹏（1988-），男，硕士，工程师，E-mail：136843440@qq.com

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