基于差异进化算法的机床加工调度优化
Yuehong Zhang1, Mianhao Zhang2
1Jinhua University of Vocational Technology, Jinhua, Zhejiang, China.
PloS one
|October 8, 2025
概括
本研究介绍了一种差异演变 (DE) 算法用于机床调度,提高生产效率和工作负载平衡. 最优化的方法有效地应对复杂的制造计划挑战.
科学领域:
- 制造业 工程 制造工程
- 运营研究 运营研究
- 计算智能是一种计算智能.
背景情况:
- 机床加工时间表对于制造效率至关重要,但是NP-hard.
- 传统的方法与大规模的,复杂的调度问题作斗争.
- 智能制造系统需要先进的优化技术.
研究的目的:
- 使用差异演化 (DE) 算法开发一个优化的机床调度方法.
- 通过专门的编码/解码来适应DE用于离散调度环境.
- 提高制造业的生产效率,资源利用和及时交付.
主要方法:
- 使用了针对离散调度而定制的差异进化 (DE) 算法.
- 为DE实施了专门的编码和解码技术.
- 在实验中将DE方法与传统启发式方法进行了比较.
主要成果:
- 提出的DE方法显著优于传统的启发式方法.
- 在madepan (完成工作的总时间) 中实现了显著的减少.
- 在机床上证明了平衡的工作负载分配.
结论:
- 不同进化 (DE) 是复杂的机床工具调度的强大而高效的工具.
- 量身定制的DE算法有效地探索可行时间表的解决方案空间.
- 这种方法对智能制造系统具有重大潜力.
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