[1]汪守斌,王 超.doi: 10.3969/j.issn.1001-3849.2025.06.002基于蚁群优化算法的电镀试验台分组式调度方法研究[J].电镀与精饰,2025,(06):9-15.
　Wang Shoubin*,Wang Chao.Research on grouped scheduling method of electroplating test bench based on ant colony optimization algorithm[J].Plating & Finishing,2025,(06):9-15.
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doi: 10.3969/j.issn.1001-3849.2025.06.002基于蚁群优化算法的电镀试验台分组式调度方法研究()

《电镀与精饰》[ISSN:1001-3849/CN:12-1096/TG]

卷:
期数:
2025年06
页码:
9-15
栏目:
出版日期:
2025-06-30

文章信息/Info

Title:
Research on grouped scheduling method of electroplating test bench based on ant colony optimization algorithm
作者:
汪守斌; 王 超
(新疆理工学院 信息工程学院,新疆 阿克苏 843100)
Author(s):
Wang Shoubin*;  Wang Chao
(School of Information Engineering, Xinjiang Institute of Technology, Aksu 843100, China)
关键词:
蚁群优化算法; 电镀任务; 试验台; 分组式调度; 图论方法; 深度优先搜索算法
Keywords:
ant colony optimization algorithm;  electroplating tasks;  test bench;  grouped scheduling;  graph theory methods;  depth first search algorithm
分类号:
TP306.1
文献标志码:
A
摘要:
电镀试验台分组式调度涉及多个试验台同时进行不同的电镀任务，每个任务有其特定的加工要求和顺序。然而，在实际操作中，由于任务分配不合理和加工顺序未优化，导致试验台之间的资源冲突、等待时间增加。为提高电镀试验台的工作效率，研究基于蚁群优化算法的电镀试验台分组式调度方法。通过基于图论的电镀试验任务分组模型，将电镀试验任务进行合理分组。利用基于蚁群优化算法的分组式调度模型，设计一个旨在实现电镀试验任务加工耗时最短化的目标函数。通过运用蚁群优化算法，求解出满足该目标函数条件的最优分组式电镀任务与仪器的加工顺序，从而实现对电镀试验台的高效分组式调度。实验结果显示：蚁群优化算法使用下，电镀试验台的仪器设备资源使用率与负载均衡度优于对比方法，能够有效优化电镀试验台资源分配效果。
Abstract:
The grouping scheduling of electroplating test benches involves multiple test benches simultaneously carrying out different electroplating tasks, each with its specific processing requirements and sequence. However, in practical operation, due to unreasonable task allocation and suboptimal processing sequence, resource conflicts and increased waiting time between test benches occur. To improve the efficiency of electroplating test benches, a grouping scheduling method based on ant colony optimization algorithm is studied for electroplating test benches. By using a graph theory based electroplating test task grouping model, the electroplating test tasks are reasonably grouped. Using a grouping scheduling model based on ant colony optimization algorithm, an objective function aimed at minimizing the processing time of electroplating test tasks is designed. By using ant colony optimization algorithm, the optimal grouping electroplating task and instrument processing sequence that meet the objective function conditions are solved, thereby achieving efficient grouping scheduling of electroplating test benches. The experimental results show that under the use of ant colony optimization algorithm, the utilization rate of instrument and equipment resources and load balancing of the electroplating test bench are better than the comparative method, which can effectively optimize the resource allocation effect of the electroplating test bench

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更新日期/Last Update: 2025-06-18