Journal of Textile Research ›› 2021, Vol. 42 ›› Issue (04): 170-176.doi: 10.13475/j.fzxb.20200500907

• Machinery & Accessories • Previous Articles     Next Articles

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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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

CLC Number: 

  • TS108

Fig.1

Improved genetic algorithm flow chart"

Tab.1

Partial workshop equipment information"

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

Tab.2

Partial workshop order information"

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

Tab.3

Influence of k on optimization results"

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

Fig.2

Comparison of initial solution results"

Fig.3

Population iteration graph"

Fig.4

Partial scheduling results Gantt chart"

Tab.4

Comparison of simulation results of different algorithms"

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
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