Journal of Textile Research ›› 2020, Vol. 41 ›› Issue (06): 36-41.doi: 10.13475/j.fzxb.20181107906

• Textile Engineering • Previous Articles     Next Articles

Spinning workshop collaborative scheduling method based on simulated annealing genetic algorithm

ZHENG Xiaohu(), BAO Jinsong, MA Qingwen, ZHOU Heng, ZHANG Liangshan   

  1. College of Mechanical Engineering, Donghua University, Shanghai 201620, China
  • Received:2018-11-28 Revised:2020-03-15 Online:2020-06-15 Published:2020-06-28

Abstract:

In order to solve the multi-objective scheduling problem of automated guided vehicle(AGV) spinning workshop collaborative scheduling system, under the four constraints of technology, processing equipment resources, AGV resources, and batch processing, an AGV spinning workshop collaborative scheduling system model that meets the minimum completion time and maximizes equipment utilization was established. Then, based on the shortcomings of simulated annealing and genetic algorithm, such as low efficiency and easy to fall into local optimal solution, a spinning scheduling system based on simulated annealing genetic algorithm was proposed. The results show that when the number of cotton drums is 50, the scheduling scheme based on simulated annealing genetic algorithm is reduced by 1 162 s and 1 619 s respectively than the simulated annealing and genetic algorithm in the same environment. The utilization rate of equipment and AGV in the yarn workshop has also increased by nearly 12% and 11% respectively. This method has application value in improving the operation efficiency of the ring spinning workshop.

Key words: simulated annealing genetic algorithm, multi-objective optimization, automated guided vehicle, spinning workshop, collaborative scheduling

CLC Number: 

  • TS112.7

Fig.1

Production process of ring spinning"

Fig.2

Simulated annealing genetic algorithm flow"

Tab.1

Equipment Utilization%"

条筒
个数
批处理机设备利用率 AGV设备利用率
SA GA SA-GA SA GA SA-GA
5 43 46 59 53 57 68
10 43 48 60 54 55 69
15 44 52 61 56 58 67
20 42 56 63 58 61 73
25 45 53 62 53 55 65
30 48 52 61 55 57 68
35 48 52 64 57 59 72
40 55 54 63 52 56 66
45 42 51 58 50 55 67
50 52 50 64 52 58 69

Tab.2

Maximum completion time and algorithm processing times"

条筒
个数
最大完工时间 算法计算时间
SA GA SA-GA SA GA SA-GA
5 1 750 2 153 1 745 11 13 12
10 2 966 3 340 2 879 26 25 26
15 4 861 5 013 3 792 35 42 40
20 6 545 6 857 4 905 48 56 55
25 7 782 8 285 6 694 60 78 81
30 8 921 9 351 7 684 74 92 88
35 9 937 10 416 8 790 97 103 104
40 10 853 11 272 9 699 108 117 115
45 11 792 12 383 10 748 124 128 126
50 12 849 13 306 11 687 143 155 138
[1] 章友鹤, 朱丹萍, 赵树超, 等. 纺纱装备的自动化、连续化、智能化和高速化[J]. 纺织导报, 2017(6):23-24.
ZHANG Youhe, ZHU Danping, ZHAO Shuchao, et al. Automation, continuation, intelligence and high speed of spinning equipment[J]. China Textile Leader, 2017(6):23-24.
[2] 阎迪. 纺织机器人的应用及发展趋势[J]. 棉纺织技术, 2017,45(9):81-84.
YAN Di. Application and development trend of textile robots[J]. Cotton Textile Technology, 2017,45(9):81-84.
[3] 胡璐璐. 两阶段混合流水车间调度问题研究[D]. 长春:吉林大学, 2015: 31-39.
HU Lulu. Research on two-stage mixed flow shop scheduling problem[D]. Changchun: Jilin University, 2015: 31-39.
[4] 刘二辉, 姚锡凡, 陶韬, 等. 基于改进花授粉算法的共融AGV作业车间调度[J/OL]. 计算机集成制造系统:1-38 [2018-11-12].
LIU Erhui, YAO Xifan, TAO Tao, et al. Integral AGV job shop scheduling based on improved flower pollination algorithm[J/OL]. Computer Integrated Manufacturing System: 1-38 [2018-11-12].
[5] 徐云琴, 叶春明, 曹磊. 含有AGV的柔性车间调度研究[J]. 计算机应用研究, 2018,35(11):3271-3275.
XU Yunqin, YE Chunming, CAO Lei. Optimization of flexible workshop scheduling with AGV[J]. Computer Applied Research, 2018,35(11):3271-3275.
[6] 王凌, 周刚, 许烨. 混合流水线调度研究进展[J]. 化工自动化及仪表, 2011,38(1):1-8.
WANG Ling, ZHOU Gang, XU Ye. Advances in the study on hybrid flow-shop scheduling[J]. Control and Instruments In Chemical Industry, 2011,38(1):1-8.
[7] 余鹏飞. 离散作业车间生产调度方法研究及其系统开发[D]. 合肥:合肥工业大学, 2017: 21-28.
YU Pengfei. Research on the production scheduling method of discrete job shop and its system develop-ment[D]. Hefei: Hefei University of Technology, 2017: 21-28.
[8] GEN M, LIN L, ZHANG H. Evolutionary techniques for optimization problems in integrated manufacturing system: state-of-the-art-survey[J]. Computers & Industrial Engineering, 2009,56(3):779-808.
[9] 李国臣, 乔非, 王俊凯, 等. 考虑能耗约束的并行机组批调度[J]. 中南大学学报(自然科学版), 2017 (8):2063-2072.
LI Guochen, QIAO Fei, WANG Junkai, et al. Parallel unit batch scheduling with energy constraints[J]. Journal of Central South University (Natural Science Edition), 2017 (8):2063-2072.
[10] LU C, XIAO S, LI X, et al. An effective multi-objective discrete grey wolf optimizer for a real-world scheduling problem in welding production[J]. Advances in Engineering Software, 2016,99:161-176.
[11] 郭乘涛, 江志斌. 应用混合蚁群算法求解并行批处理机组批与调度问题[J]. 上海交通大学学报, 2010,44(8):1068-1073.
GUO Chengtao, JIANG Zhibin. Application of hybrid ant colony algorithm to solve parallel batch batch and scheduling problems[J]. Journal of Shanghai Jiaotong University, 2010,44(8):1068-1073.
[12] 王娜. 基于改进蚁群算法的多AGV作业调度研究[D]. 西安: 西安工程大学, 2017: 21-25.
WANG Na. Research on multi-AGV job scheduling based on improved ant colony algorithm[D]. Xi'an, Xi'an Polytechnic University, 2017: 21-25.
[13] SALIDO M A, ESCAMILLA J, GIRET A, et al. A genetic algorithm for energy-efficiency in job-shop scheduling[J]. International Journal of Advanced Manufacturing Technology, 2016,85(5-8):1-12.
[14] 黄海松, 刘凯, 初光勇. 改进模拟退火算法在柔性调度中的应用[J]. 组合机床与自动化加工技术, 2018(2):148-151,156.
HUANG Haisong, LIU Kai, CHU Guangyong. Application of improved simulated annealing algorithm in flexible scheduling[J]. Combined Machine Tool & Automatic Processing Technology, 2018(2):148-151,156.
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