| 基于改进遗传算法的模具零件孔群加工路径优化 |
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| 引用本文： | 杨彩虹,林守金,杨明.基于改进遗传算法的模具零件孔群加工路径优化[J].河北工业科技,2019,36(2):91-97. |
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| 作者姓名： | 杨彩虹 林守金 杨明 |
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| 作者单位： | 中北大学理学院,山西太原 030051;信息探测与处理山西省重点实验室,山西太原 030051;中山迈雷特数控技术有限公司,广东中山,528437 |
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| 基金项目： | 国家自然科学基金(61601412,61571404,61471325) |
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| 摘 要： | 为提高孔群模具的加工效率,提出了一种最近邻、遗传算法和禁忌搜索相融合的改进遗传算法。采用最近邻算法选取一系列好的初始种群,同时将禁忌搜索中"禁忌"的思想引入到遗传算法中,并在进化过程中随机引入部分新个体,进行迭代搜索。根据孔群加工特点建立了类似旅行商问题的数学模型,并用改进算法求解最短加工路径,在分布复杂的孔类模具上进行数值实验。轮胎实例应用结果表明,改进算法优化后路径长度比CAM系统算法优化后路径长度缩短5.31%,比X向路径法缩短77.88%,比Y向路径法缩短77.63%,比最近邻算法缩短4.52%;当实验参数相同时,改进算法路径长度比遗传算法缩短14.65%,且运行时间平均缩短了63.60%。改进算法的路径长度明显缩短,有效提高了孔群的数控加工效率。其通用性较好,在提升数控系统孔群加工效率方面具有参考价值。
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| 关 键 词： | 应用数学 孔群加工 最近邻 禁忌搜索 遗传算法 |
| 收稿时间： | 2018/12/4 0:00:00 |
| 修稿时间： | 2019/2/20 0:00:00 |
Optimization of hole group path planning for mold part based on improved genetic algorithm |
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| YANG Caihong,LIN Shoujin and YANG Ming.Optimization of hole group path planning for mold part based on improved genetic algorithm[J].Hebei Journal of Industrial Science & Technology,2019,36(2):91-97. |
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| Authors: | YANG Caihong LIN Shoujin and YANG Ming |
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| Abstract: | In order to improve the drilling efficiency of hole group for mold part, an improved genetic algorithm combining nearest neighbor, genetic algorithm and taboo search is proposed. The nearest neighbor algorithm is adopted to select a series of good initial populations, simultaneously the taboo search is introduced into the genetic algorithm, and some new individuals are randomly introduced in the evolution process to search optimal solution. Based on the drilling characteristics of the hole group, a mathematical model similar to the tsp is established and the improved algorithm is used to solve the drilling problem, and the experiments on the complex hole mold is carried out. The tire experiment results show that the path length of the improved algorithm is 5.31% shorter than that of the CAM system algorithm, 77.88% shorter than the X-path method''s, 77.63% shorter than the Y-path method''s, and 4.52% shorter than the nearest neighbor algorithm''s. When the parameters are the same, the path length of the improved algorithm is 14.65% shorter than that of the genetic algorithm, and the running time is 63.60% shorter, showing that the improved algorithm can effectively improve the NC drilling efficiency of the hole group. The path length of the hole group for mold part based on the improved genetic algorithm is obviously shorter, and the algorithm has good versatility, providing some reference in improving the drilling efficiency of hole group with numerical control system. |
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| Keywords: | applied mathematics hole group drilling nearest neighbor taboo search genetic algorithm |
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