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作 者:孔志学 姜恒[1] 张珠峰 Kong Zhixue;Jiang Heng;Zhang Zhufeng(Shanghai Spaceflight Precision Machinery Institute,Shanghai 201600)
出 处:《航天制造技术》2021年第4期17-23,50,共8页Aerospace Manufacturing Technology
摘 要:针对多品种小批量数控加工生产线,不同工件、多种工艺路线在同一条生产线上进行混合生产时生产线节拍低、设备利用率低的问题,提出了一种迭代渐进式蚁群算法对生产线最优加工方案进行选择。基于时序优先原则,按工艺路线串行、设备资源使用时间连续的准则,建立生产线时间模型及生产线综合评价指标;改进算法流程,限定初代算法规模,快速遍历所有产品加工路线,再逐步扩大算法规模,根据历代最优解不同工艺路线分布情况,对蚂蚁路径距离值进行更新,采用至今最优蚂蚁信息素叠加扩散策略,促使搜索进程加速向最优解收敛;采用低阈值伪随机算法,提高算法全局搜索能力,避免算法后期陷入局部最优解。在VS2015软件平台上进行算法仿真对比,结果表明,该算法在避免局别最优和算法收敛速度方面具有明显优势。In order to solve the problems of low production cycle and low equipment utilization when different workpieces with multiple process routes are processed on the multi-variety and small batch CNC machining production line,an iterative progressive ant colony algorithm is proposed to select the optimal processing plan of the production line.Based on the principle of time sequence priority,the process route serialization and equipment resource usage time continuous criteria,establish production line time model and production line comprehensive evaluation index;improve the algorithm process,first,limit the scale of the first generation algorithm,quickly traverse all product processing routes,and then gradually expand the algorithm scale.According to the distribution of different process routes of the best solutions in the past generations,update the ant path distance value,adopting the best ant pheromone superposition diffusion strategy so far,to promote the search process to accelerate the convergence to the optimal solution;using a low-threshold pseudo-random algorithm to improve the algorithm’s global search ability and avoid the algorithm from falling into the local optimal solution in the later stage.On the VS2015 software platform,the algorithm simulation comparison is conducted.The results show that the algorithm has great improvement in avoiding local optimization and accelerating convergence speed.
关 键 词:生产线时间模型 迭代渐进式蚁群算法 时间线排序 工艺路线
分 类 号:TP274[自动化与计算机技术—检测技术与自动化装置]
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