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Connector-based approach to assembly planning using a genetic algorithm

机译:使用遗传算法的基于连接器的装配计划方法

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摘要

Assembly planning refers to the task where planners arrange a specific assembly sequence according to the product design description as well as to their particular heuristics in putting together all the components of a product. In assembly planning, one needs to take into consideration the relationships between components such as the geometric limitation factor before the precedence sequence is set up for assembly. This deliberation will contribute strongly to lower the production cost. Unlike traditional studies where the liaison graph goes with a genetic algorithm, an attempt is made to solve problems in assembly planning by using a genetic algorithm under the connector-based environment. Such a connector-based genetic algorithm takes a more realistic view. The key point in this approach to assembly planning is to combine the connector concept and characteristics of a genetic algorithm using object-oriented programming; thus, the programming language C++ is used to develop the mechanism of the algorithm. Finally, a stapler and a computer hard disk were used as practical examples to illustrate the possibility of such an idea. Consequently, in terms of assembly planning, it is feasible to create a genetic algorithm based on the connector's engineering features.
机译:组装计划是指计划人员根据产品设计说明及其将产品的所有组件组合在一起的特定启发式方法安排特定组装顺序的任务。在装配计划中,在设置优先顺序进行装配之前,需要考虑零件之间的关系,例如几何限制因素。这项审议将大大有助于降低生产成本。与传统研究中联络图与遗传算法一起使用的传统研究不同,尝试在基于连接器的环境下使用遗传算法来解决装配计划中的问题。这种基于连接器的遗传算法采取了更为现实的观点。这种装配计划方法的重点是使用面向对象的编程将连接器的概念和遗传算法的特征相结合。因此,使用编程语言C ++来开发算法的机制。最后,使用订书机和计算机硬盘作为实际示例来说明这种想法的可能性。因此,就装配计划而言,根据连接器的工程特征创建遗传算法是可行的。

著录项

  • 来源
    《International Journal of Production Research》 |2004年第11期|p.2243-2261|共19页
  • 作者单位

    Department of Industrial Engineering, Da Yeh University, 112 Shan-Jiau Road, Da-Tsuen, Chang-hua, 515, Taiwan, Republic of China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 管理学;
  • 关键词

  • 入库时间 2022-08-17 13:43:45

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