生产设备和RGV的双重资源集成调度问题的多目标优化,考虑无冲突路由问题
Qinglei Zhang1,2, Jing Hu2, Zhen Liu2
1China Institute of FTZ Supply Chain, Shanghai Maritime University, Shanghai, China.
PloS one
|January 26, 2024
概括
这项研究引入了一个新的调度模型,用于灵活的工作车间问题,优化生产设备和车辆路线,以尽量减少完成时间. 改进的灰狼优化器在解决复杂的调度挑战方面表现出卓越的性能.
科学领域:
- 运营研究 运营研究
- 工业工程 工业工程 工业工程
- 人工智能的人工智能
背景情况:
- 灵活的工作车间安排问题 (FJSP) 对于生产效率至关重要.
- 双向轨道制导车辆 (RGV) 的碰撞避免影响了调度和效率.
- RGV调度与生产设备分配密切相关.
研究的目的:
- 为生产设备和RGVs提出一个双资源集成调度模型.
- 在FJSP中解决无冲突路由问题 (CFRP).
- 为了尽量减少RGV和产品的最大完成时间.
主要方法:
- 开发一个多目标改进的离散灰狼优化器 (MOID-GWO).
- 与已建立的多目标进化算法 (MOEA) 进行比较分析,如NSGA-II,SPEA2和MOPSO.
- 验证使用42个不同的问题实例和现实世界的案例研究.
主要成果:
- MOID-GWO在代际距离 (GD),反向GD (IGD) 和跨多个实例的Spread指标方面表现优于比较算法.
- 该算法实现了更好的融合和多样性 (CD),帕雷托边界更接近最佳解决方案.
- 拟议的模型和算法通过建筑机械零部件生产实例进行了验证.
结论:
- 拟议的双资源集成调度模型有效地解决了FJSP与CFRP.
- MOID-GWO是一种高效的算法,用于解决复杂的,多目标的调度问题.
- 该方法通过优化RGV路由和设备分配来提高生产效率.
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