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

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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
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