纺织学报 ›› 2021, Vol. 42 ›› Issue (04): 170-176.doi: 10.13475/j.fzxb.20200500907

• 机械与器材 • 上一篇    下一篇

纬编织造车间生产调度方法研究

周亚勤(), 王攀, 张朋, 张洁   

  1. 东华大学 机械工程学院, 上海 201620
  • 收稿日期:2020-05-06 修回日期:2020-12-30 出版日期:2021-04-15 发布日期:2021-04-20
  • 作者简介:周亚勤(1977—),女,副教授,博士。主要研究方向为智能制造、生产计划与调度。E-mail: zhouyaqin@dhu.edu.cn。
  • 基金资助:
    国家自然科学基金资助项目(51435009)

Research on production scheduling method for weft knitting workshops

ZHOU Yaqin(), WANG Pan, ZHANG Peng, ZHANG Jie   

  1. College of Mechanical Engineering, Donghua University, Shanghai 201620, China
  • Received:2020-05-06 Revised:2020-12-30 Online:2021-04-15 Published:2021-04-20

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摘要：

为解决纬编织造车间生产订单品种繁多、工艺复杂等问题,构建综合考虑织造车间因素的生产调度模型。研究了“订单拆分-设备选择-任务排序”的织造车间调度方法设计订单拆分规则,对重要客户交货期紧急的订单进行拆分处理;基于产品工艺相似性设计启发式规则,对产品加工设备进行选择;设计结合变邻域搜索策略的遗传算法,对设备加工任务进行优化排序。结果表明:通过提出的调度方法,保证了产品交货期内的加工时间富裕度,减少了设备改机时间,实现了产品完工时间与总拖期时间最小化目标。以生产实例进行算法仿真分析,验证本文方法及算法的有效性,并对不同规模案例与其他算法的求解结果进行比较,验证了改进遗传算法的优越性。

关键词: 纬编生产, 织造车间, 生产调度, 订单拆分, 改进遗传算法

Abstract:

A weft knitting workshop is order-oriented with a wide range of product types and complex processes for the production, a comprehensive production scheduling model for weft knitting workshop was constructed to address the problems. The scheduling method of "order split-equipment selection-task sequencing" was adopted for this study. Order splitting rules was firstly made to split the orders of important customers with urgent delivery dates. Based on product process similarity, heuristic rules was established to select product processing equipment. Genetic algorithm combined with variable neighborhood search strategy was designed to optimize the sorting of equipment processing tasks. Through the proposed scheduling method, the abundance of processing time during the product delivery period is guaranteed, the time for equipment modification is reduced, and the goal of minimizing product completion time and total delay time is achieved. Simulation analysis of the algorithm is carried out in a weft-knitting enterprise to verify the effectiveness of the rules and algorithms proposed in this paper. By comparing the results of different scale cases with that from using other algorithms, the superiority of the improved genetic algorithm is verified.

Key words: weft knitting production, weft knitting workshop, production scheduling, order split, improved genetic algorithm

中图分类号: 

  • TS108

图1

改进遗传算法流程图"

表1

车间设备信息(节选)"

设备代号 数量/台 设备号 日产能/kg
M1 2 M01/M02 45
M2 2 M03/M04 60
M3 2 M05/M06 50
M4 2 M07/M08 40

表2

车间订单信息(节选)"

订单编号 产品
编号		 客户
重要度		 产品数
量/kg		 面料
类型		 交货期/
d
D181121001 1 10 115 罗纹 16
D181121001 2 10 80 提花 14
D181121001 3 10 750 平纹 10
… … … … … …
D181121004 11 6 165 罗纹 23
D181121004 12 6 196 提花 12
… … … … … …
D181121008 30 8 810 提花 14
D181121008 31 8 75 罗纹 28
D181121008 32 8 65 平纹 23

表3

不同k值对优化结果的影响"

k 目标函数值f 平均改机次数
1 3.6 3.0
2 4.2 3.5
3 5.3 3.0
4 4.8 3.8
5 3.8 4.2
6 2.3 4.8

图2

初始解结果对比图"

图3

种群迭代变化图"

图4

部分调度结果甘特图"

表4

不同算法仿真结果对比"

案例规模 适应度函数值f 平均收敛代数
GA SAGA VGA IGA GA SAGA VGA IGA
best avg best avg best avg best avg
4*4*20 3.65 2.65 3.71 2.87 4.95 4.14 5.13 4.34 91.5 65.0 70.2 50.4
4*5*20 3.71 2.67 3.81 2.91 4.95 4.18 5.19 4.36 89.3 60.2 64.3 44.2
4*6*20 3.74 2.68 3.82 2.95 4.98 4.23 5.21 4.39 87.1 58.7 64.2 41.9
4*4*30 3.63 2.59 3.68 2.84 4.93 4.09 5.11 4.28 99.4 76.4 78.1 59.1
4*5*30 3.66 2.62 3.72 2.86 4.97 4.15 5.17 4.33 94.5 71.8 72.6 56.7
4*6*30 3.70 2.64 3.74 2.89 5.01 4.15 5.20 4.37 91.6 65.3 66.4 50.2
[1] MARIA H, PURUSHOTMAN D, MAHBOD A. Scheduling non-identical parallel batch processing machines to minimize total weighted tardiness using particle swarm optimization[J]. Computers & Industrial Engineering, 2017,113:425-436.
[2] JOSE E C A, JOSEPH Y T L. Scheduling unrelated parallel batch processing machines with non-identical job sizes and unequal ready times[J]. Computers and Operations Research, 2017,78:117-128.
[3] SUHAIMI N, NGUYEN C, DAMODARAN P. Lagrangian approach to minimize makespan of non-identical parallel batch processing machines[J]. Computers & Industrial Enginering, 2016,101:295-302.
[4] 赵晴瑶. 基于改进果蝇优化算法的混合流水车间调度方法研究[D]. 武汉:华中科技大学, 2018: 39-50.
ZHAO Qingyao. Study on scheduling method of mixed flow shop based on improved fruit fly optimization algorithm[D]. Wuhan:Huazhong University of Science and Technology, 2018: 39-50.
[5] 周亚勤, 李蓓智, 杨建国. 考虑批量和辅助时间等生产工况的智能调度方法[J]. 机械工程学报, 2006(1):56-60.
ZHOU Yaqin, LI Beizhi, YANG Jianguo. Intelligent scheduling method considering production conditions such as batch and auxiliary time[J]. Journal of Mechanical Engineering, 2006(1):56-60.
[6] WANG Jingan, PAN Ruru, GAO Weidong, et al. An automatic scheduling method for weaving enterprises based on genetic algorithm[J]. Journal of The Textile Institute, 2015,106(12):1-11.
[7] 孙延. 基于蚁群算法的纺织企业生产调度技术研究[J]. 电子设计工程, 2015,23(18):116-118.
SUN Yan. Research on production scheduling technology of textile enterprises based on ant colony algorithm[J]. Electronic Design Engineering, 2015,23(18):116-118.
[8] 孟朔, 潘如如, 高卫东, 等. 采用主目标进化遗传算法的织造排程研究[J]. 纺织学报, 2019,40(8):169-174.
MENG Shuo, PAN Ruru, GAO Weidong, et al. Study on weaving schedule using master objective evolutionary genetic algorithm[J]. Journal of Textile Research, 2019,40(8):169-174.
[9] YILMAZ E D, OZMUTLU H C. Solution method for a large-scale loom scheduling problem with machine eligibility and splitting property[J]. Journal of The Textile Institute, 2017,108(12):2154-2165.
[10] 白俊峰, 贾志浩, 白一辰. 基于改进遗传算法的车间调度问题研究[J]. 现代制造技术与装备, 2019(12):198-200.
BAI Junfeng, JIA Zhihao, BAI Yichen. Research on workshop scheduling based on improved genetic algorithm[J]. Modern Manufacturing Technology and Equipment, 2019 (12):198-200.
[11] 卢颖涛. 针织企业染整车间调度方法研究[D]. 上海:东华大学, 2019: 23-25.
LU Yingtao. Research on dyeing and finishing workshop scheduling methods for knitting enterprises[D]. Shanghai: Donghua University, 2019: 23-25.
[12] 何桂霞. 特殊工艺约束下最小完工时间并行多机调度问题的研究[J]. 浙江工业大学学报, 2010,38(1):63-66,94.
HE Guixia. Study on minimum completion time parallel multi-machine scheduling problem under special process constraints[J]. Journal of Zhejiang University of Technology, 2010,38(1):63-66,94.
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