• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2023, Vol. 59 ›› Issue (5): 235-246.doi: 10.3901/JME.2023.05.235

• 数字化设计与制造 • 上一篇    下一篇

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面向不确定性的车间布局调度集成建模与优化

王亚良, 高康洪, 范欣宇, 金寿松   

  1. 浙江工业大学机械工程学院 杭州 310023
  • 收稿日期:2022-03-15 修回日期:2022-09-28 出版日期:2023-03-05 发布日期:2023-04-20
  • 通讯作者: 金寿松(通信作者),男,1965年出生,博士,副教授。主要研究方向为智能制造、机械设计。E-mail:jinshs@zjut.edu.cn
  • 作者简介:王亚良,男,1977年出生,博士,正高级实验师。主要研究方向为生产系统优化、智能制造。E-mail:wangyaliang@zjut.edu.cn
  • 基金资助:
    国家重点研发计划(2018YFB1308100)、浙江省自然科学基金(LY16G010013)和国家高技术研究发展计划(863计划,2015AA0430020)资助项目。

Uncertainty-oriented Workshop Layout and Scheduling Integration Optimization

WANG Yaliang, GAO Kanghong, FAN Xinyu, JIN Shousong   

  1. College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023
  • Received:2022-03-15 Revised:2022-09-28 Online:2023-03-05 Published:2023-04-20

摘要: 针对制造系统的不确定性和车间布局调度协同优化难题,研究了不确定环境下车间布局调度集成优化问题,旨在耦合车间布局调度中的不确定因素,实现制造系统的高效有序运作。选取工件需求、工序加工时间和设备故障作为影响布局调度集成优化的不确定因素,构建以制造过程中总费用、总完工时间最小和鲁棒指标最大为优化目标的面向不确定性的车间布局调度集成优化模型。设计了一种具有改进选择算子的NSGA-III(NSGA-III with improved selection operator, NSGA-III-ISO),改进选择算子增强了算法的全局搜索能力和稳定性,同时引入PBI距离并改进其极小值取值方法。通过基准函数测试结果表明,新算法具有更好的前端分布性和收敛性。将集成模型和改进的求解算法应用于车间布局调度工程实例,其结果进一步验证了模型和算法的有效性和可行性。

关键词: 不确定性因素, 布局调度集成建模, 改进的NSGA-III, 多目标优化

Abstract: According to the uncertainty of manufacturing system and the integration optimization problem of workshop layout and scheduling, the integrated optimization of workshop layout and scheduling under uncertain environment is studied, which realized the efficient and orderly operation of manufacturing system by coupling the uncertain factors in shop floor scheduling. The uncertain factors including the workpiece requirements, processing time and equipment failures are selected, which affecting the integrated optimization of layout and scheduling. An uncertainty-oriented workshop layout scheduling integration optimization model is constructed, which taking the minimum total cost, total completion time and maximum robust indexes in the manufacturing process as the optimization objectives. An algorithm called NSGA-III with improved selection operator (NSGA-III-ISO) is designed, which could enhance the global search capability and stability of the algorithm. At the same time, PBI distance is introduced and the method of determining a minimum is improved. The effectiveness of NSGA-III-ISO is verified by DTLZ series test functions and numerical examples. Finally, the integrated model and the improved algorithm are applied to a workshop layout scheduling engineering example, and the results further verified the validity and feasibility of the model and algorithm.

Key words: uncertainty factors, layout and scheduling integrated optimization modeling, improved NSGA-III algorithm, multi-objective optimization

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