相关实验视频
Updated: May 23, 2025

Operation of the Collaborative Composite Manufacturing CCM System
Published on: October 1, 2019
一个代的贪的算法,用于解决一个多目标分布式组装灵活的工作车间调度问题与模糊的处理时间
本研究引入了一种新的算法,用于灵活的工厂调度问题,处理时间不确定. 拟议的方法有效地减少了生产时间和能源消耗,优于现有的方法.
科学领域:
- 运营研究 运营研究
- 制造业 工程 制造工程
- 人工智能的人工智能
背景情况:
- 由于固有的不确定性,决定性处理时间对于现实的制造是不够的.
- 灵活的工作车间调度问题 (FJSP) 是复杂的,特别是分布式组装和不确定的参数.
研究的目的:
- 为了解决多目标分布式组装灵活的工作车间安排问题,使用类型-2模糊时间 (DAT2FFJSP).
- 在生产计划中优化制造范围和总能耗.
主要方法:
- 开发了一个混合整数线性编程模型.
- 提出了一个基于人口的代贪算法 (PBIGA),与Q学习机制集成.
- 关键功能包括混合初始化,多种搜索运营商,运营商选择的Q学习和节能策略.
主要成果:
- 与最先进的算法相比,PBIGA表现出卓越的性能.
- 在30个实例上进行了广泛的实验,验证了拟议组件和整体算法的有效性.
结论:
- 开发的PBIGA有效地处理了灵活的工作室安排中的不确定性.
- 该方法成功地优化了产品范围和能源消耗,在该领域取得了重大进展.
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