使用改进的NSGA-II进行多目标优化,用于大型门加工车间的综合工艺规划和调度问题
Junqiang Wang1,2, Lihua Xu1,2, Shuangqiu Sun1,2
1Department of Mechanical and Electrical Engineering, Hebei Vocational University of Technology and Engineering, Xingtai, China.
PloS one
|June 25, 2024
概括
本研究提出了一种改进的算法,用于大型门制造的综合工艺规划和调度 (IPPS). 增强的NSGA-II算法优化了生产,以减少复杂车间的产量和成本.
科学领域:
- 制造业 工程 制造工程
- 运营研究 运营研究
- 工业工程 工业工程 工业工程
背景情况:
- 大型门生产涉及复杂的,小批量制造各种各样的零件.
- 在一个车间同时生产多种门型号和尺寸,会带来重大调度挑战.
- 在这种情况下,集成过程规划和调度 (IPPS) 问题是一个大规模的,NP-hard的组合优化挑战.
研究的目的:
- 开发和验证一种有效的方法来解决大型门制造中的IPPS问题.
- 通过尽量减少制造和降低制造成本,提高生产效率.
- 为了弥合理论IPPS研究和实际的工业应用之间的差距.
主要方法:
- 为IPPS开发了一种改进的非主导排序遗传算法II (NSGA-II).
- 在算法中采用了两部分编码和插入贪解码方法.
- 使用动态人口更新策略和适应性突变技术来提高解决方案的质量和多样性.
主要成果:
- 拟议的NSGA-II算法成功地获得了对制造商和制造成本的满意解决方案.
- 该方法在Yuanda Valve Company的一项现实实例研究中证明了它的有效性.
- 实施的方法考虑了现实的制造约束,提高了实际适用性.
结论:
- 改进的NSGA-II算法为大型门制造中的复杂IPPS问题提供了可行的解决方案.
- 集成动态人口更新和自适应突变可以提高算法性能.
- 该研究成功地展示了先进的优化技术在实际制造环境中的实际应用.
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