一个双阶段改进的变量邻里搜索-正弦共弦算法,用于安全考虑的多行布局问题
Achmad Pratama Rifai1, Wangi Pandan Sari2
1Department of Mechanical and Industrial Engineering, Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta, Indonesia. achmad.p.rifai@ugm.ac.id.
Scientific reports
|November 14, 2025
概括
本研究引入了多行布局问题 (MRLP) 的新算法,考虑了安全通关. 改进的可变邻域搜索-正弦共弦算法 (IVNS+SCA) 有效地降低了成本,并改善了工业环境中的机器放置.
科学领域:
- 运营研究 运营研究
- 工业工程 工业工程 工业工程
- 优化优化 优化优化
背景情况:
- 多行布局问题 (MRLP) 对于最小化工业环境中的物料处理成本至关重要.
- 现有的MRLP模型往往忽视了要求机器之间的最小距离的安全规定.
- 这种差距需要一种MRLP方法,该方法整合了安全许可限制.
研究的目的:
- 通过纳入安全因素来解决现有的MRLP研究的局限性.
- 提出一种新的两阶段算法,以解决安全考虑的MRLP.
- 提高工业环境中的机器放置策略.
主要方法:
- 一种两阶段的优化方法,结合了改进变量邻近搜索 (IVNS) 和正弦共弦算法 (SCA).
- 第1阶段 (IVNS):确定所有行中的初始机器位置.
- 第二阶段 (SCA):完善机器放置以获得最佳解决方案.
主要成果:
- 拟议的IVNS+SCA算法证明了在解决MRLP与安全因子方面的有效性和效率.
- 与基准metaheuristics相比,计算测试显示了0.9-5.3%的平均改善.
- 在大型问题实例中观察到显著的性能增长.
结论:
- 通过整合安全许可,IVNS+SCA算法为MRLP提供了一种优越的方法.
- 这种方法为工业布局设计提供了实际的好处,提高了成本效益和安全性.
- 算法的性能验证了其适用于复杂的,现实世界的布局问题.
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