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处理-运输复合机器人的能源效率高的灵活工厂调度问题
Meizhou Zhang1,2, Min Zhou1,2, Liping Zhang3,4
1Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan, 430081, China.
Scientific reports
|September 5, 2025
概括
这项研究介绍了制造业中加工运输机器人的节能调度. 一个新的算法可以最大限度地减少灵活工厂的能源消耗和生产时间.
科学领域:
- 制造系统工程
- 运营研究
- 人工智能
背景情况:
- 在制造业中越来越多地使用加工运输复合机器人,导致能源需求增加.
- 有效的调度对于管理这些复杂系统的能源消耗至关重要.
- 灵活的工作场所环境对集成机器人安排提出了独特的挑战.
研究的目的:
- 在灵活的工作车间研究机器人机器集成的节能调度.
- 为了最大限度地减少能源消耗,
- 解决与先进制造机器人相关的日益增长的能源消耗.
主要方法:
- 开发一种新的混合整数线性编程 (MILP) 模型.
- 一个双自学共进化算法的提议.
- 使用三维解决方案表示和贪的解码策略.
- 采用混合初始化方法与适应性随机选择和混乱映射.
- 实施双重自学机制,以进行演化操作者选择和群体相互作用.
主要成果:
- 提出的MILP模型有效地阐述了节能调度问题.
- 双自学共进化算法在最大限度地减少能源消耗和寿命方面表现出卓越的性能.
- 实验分析证实了拟议的算法及其组件的有效性.
- 这种贪的解码策略成功地减少了置时间和能源消耗.
结论:
- 开发的方法为机器人机器集成的灵活工作室提供了有效的节能调度解决方案.
- 新的算法及其组件显著改善了优化结果.
- 这项研究通过减少能源消耗为可持续制造业做出了贡献.
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