机械工程学报 >

2018 , Vol. 54 >Issue 9: 45 - 54

DOI: https://doi.org/10.3901/JME.2018.09.045

特邀专栏：航天先进制造技术专栏

面向节能的导弹结构件混线生产作业车间多目标调度研究

  • 魏鑫 ,
  • 张泽群 ,
  • 唐敦兵 ,
  • 杨长祺 ,
  • 金永乔 ,
  • 秦威
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  • 1. 南京航空航天大学机电学院 南京 210016;
    2. 上海航天技术研究院上海航天精密机械研究所 上海 201600;
    3. 上海交通大学机械与动力工程学院 上海 200240
魏鑫,男,1992年出生。主要研究方向为车间调度。E-mail:weix_mail@163.com;张泽群,男,1991年出生,博士研究生。主要研究方向为智能制造系统研究与设计。E-mail:a15850589231@163.com;唐敦兵,男,1972年出生,教授,博士研究生导师。主要研究方向为智能制造系统、制造系统与自动化、数字化设计与制造。E-mail:d.tang@nuaa.edu.cn;金永乔,男,1983年出生,博士。主要研究方向为高档装备研制及智能制造系统。E-mail:kerrking@163.com;秦威,男,1982年出生,博士,讲师。主要研究方向为复杂制造系统的建模、控制与优化。E-mail:wqin@sjtu.edu.cn

收稿日期: 2017-08-02

  修回日期: 2018-01-10

  网络出版日期: 2018-05-05

基金资助

国家自然科学基金（U1637211）、航空科学基金（20161652015）、中央高校基本科研业务费专项基金（56XBA17006）和江苏省青蓝工程资助项目。

收起

Energy-saving Oriented Multi-objective Shop Floor Scheduling for Mixed-line Production of Missile Components

  • WEI Xin ,
  • ZHANG Zequn ,
  • TANG Dunbing ,
  • YANG Changqi ,
  • JIN Yongqiao ,
  • QIN Wei
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  • 1. College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016;
    2. Shanghai Spaceflight Precision Machinery Institute, Shanghai Academy of Spaceflight Technology, Shanghai 201600;
    3. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240

Received date: 2017-08-02

  Revised date: 2018-01-10

  Online published: 2018-05-05

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摘要

针对导弹结构件混线生产过程中具有的型号多、工艺复杂、生产能耗大、交货期紧的特性，以能量消耗和完工时间为目标，建立了基于设备-能耗曲线的柔性作业车间混线生产系统的数学调度模型。提出了一种双元混合的改进遗传算法对该调度模型进行求解，具体包括：引入粒子群算法的信息共享机制，对遗传算法的交叉算子进行改进，提高算法的寻优能力；用Hill函数构建传统模拟退火的温度更新函数，替代遗传算法的变异部分，以弥补遗传算法容易陷入早熟收敛的不足。采用多指标加权灰靶决策模型从得到的一组Pareto解集中选择最满意调度方案。分别用完全柔性和部分柔性的作业实例对算法进行验证，证明了改进算法的有效性。最后，将算法用于上海航天精密机械研究所结构件生产车间的生产实例，取得了较好生产的指导效果。

关键词： 设备状态-能耗曲线; 柔性作业车间; 能量消耗; 双元混合改进遗传算法; 多指标加权灰靶决策模型

本文引用格式

魏鑫 , 张泽群 , 唐敦兵 , 杨长祺 , 金永乔 , 秦威 . 面向节能的导弹结构件混线生产作业车间多目标调度研究[J]. 机械工程学报, 2018 , 54(9) : 45 -54 . DOI: 10.3901/JME.2018.09.045

Abstract

Aimed at the characteristics of multi-project production, complex process, high energy consumption and tight delivery in the mix-line production of missile structural components, an optimization model for a flexible job-shop scheduling problem considering energy consumption and makespan is developed based on equipment state-energy-consumption curve. A binary hybrid improved genetic algorithm (BH-GA) is proposed to solve the established optimization problem. To improve the searching ability of the algorithm, an information-sharing mechanism based on particle swarm optimization (PSO) is introduced to design the crossover operation of genetic algorithm (GA). In order to avoid falling into local optical solution, a novel temperature update function of simulated annealing algorithm (SA) based on Hill function is used to replace the mutation operation of GA. In addition, a weighted multi-attribute grey target decision model is adopted to select the most satisfactory schedule scheme. The effectiveness of the proposed algorithm is verified by the completely and partially flexible scheduling problems. Finally, the proposed algorithm is applied to the production workshop of missile structural components at an aerospace institute in Shanghai, and good effect is gained.

Key words： equipment state-energy-consumption curve; flexible job-shop; energy consumption; binary hybrid improved genetic algorithm; weighted multi-attribute grey target decision model

参考文献

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