Journal of Textile Research ›› 2022, Vol. 43 ›› Issue (06): 151-156.doi: 10.13475/j.fzxb.20210507606

• Apparel Engineering • Previous Articles     Next Articles

A duo-directional recommendation strategy for order-production oriented to apparel supply chain platforms

CHEN Qingting1, DU Jinsong1(), LIN Xiang2, ZHU Jianlong3   

  1. 1. College of Fashion and Design, Donghua University, Shanghai 200051, China
    2. School of Computer Science, Fudan University, Shanghai 200433, China
    3. Hla Group Co., Ltd., Wuxi, Jiangsu 214426,China
  • Received:2021-05-27 Revised:2021-12-06 Online:2022-06-15 Published:2022-07-15
  • Contact: DU Jinsong E-mail:ducccp@dhu.edu.cn

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Abstract:

Aiming at the problem of duo-directional recommendation between multiple production orders of clothing and multiple manufacturers on the clothing supply chain platform, the transaction needs of the ordering party and the manufacturer were analyzed as the first step in this research, followed by the construction of the utility evaluation index structure and preference utility function of both parties. Based on preference ranking, the Gale-Shapley (GS) algorithm strategy is adopted to establish a duo-directional matching model for apparel production orders. Data from 6 ordering companies and 6 manufacturers were used to carry out a duo-directional matching model experiment, which verified the stability and acceptability of the matching results. The expert questionnaire survey shows that the average acceptance rate of the ordering parties reached 94%, and the average acceptance rate of the order receiving parties reached 89%. The results show that the duo-directional matching model based on the order utility evaluation system and the GS strategy can fully reflect the ordering party's transaction needs and the manufacturer's willingness to accept orders. Taking into account the transaction needs of both parties in trading, the matching model, as on the third-party clothing supply chain platform, can effectively improve the accuracy and stability of the matching recommendation results for order allocation and order acceptance.

Key words: Gale-Shapley algorithm, apparel supply chain platform, duo-directional matching of orders, clothing order matching

CLC Number: 

  • TS941

Fig.1

Platform-based order matching mechanism"

Tab.1

Preference index of trading parties"

交易
双方		 一级指标要素 二级指标内容 权重 权重
数值
下单方 款式关联需求 Z i j 1 版型风格关联度 X i j 1 a i 1 0.181 82
工艺关联度 X i j 2 a i 2 0.151 52
质量价格比 X i j 3 a i 3 0.171 72
服务能力需求 Z i j 2 设计研发能力 X i j 4 a i 4 0.181 82
企业管理能力 X i j 5 a i 5 0.141 41
综合供应链能力 X i j 6 a i 6 0.171 72
接单方 可生产性 N j i 1 交期要求 Y j i 1 — —
起订量要求 Y j i 2 — —
可盈利性 N j i 2 盈利需求 Y j i 3 — —

Tab.2

Supporting data content from trading parties and the valuations"

交易方 支撑数据内容 参数 赋值说明
下单方
(订单 O i)		 订单款式版型风格类型 O i 1 按分类赋值,例如休闲=1,商务=2,……
订单款式加工工艺类型 O i 2 按分类赋值,例如印花=1,刺绣=2,……
订单生产质量要求 O i 3 10分制赋值,从低到高(0~10分)评估
订单批量 O i 4 根据实际月销量数值取整
订单清加工最高报价 O i 5 售价/定倍率,如本文研究的定倍率为5
接单方
(制造商 S j)		 可加工服装风格类型 S j 1 按分类赋值,例如休闲=1,商务=2,……
可加工工艺类型 S j 2 按分类赋值,例如印花=1,刺绣=2,……
加工质量水平 S j 3 10分制赋值,从低到高(0~10分)评估
设计研发能力 S j 4 10分制赋值,从低到高(0~10分)评估
生产管理能力 S j 5 10分制赋值,从低到高(0~10分)评估
供应链综合能力 S j 6 10分制赋值,从低到高(0~10分)评估
剩余产能 S j 7 实际数值
订单最小起订量 S j 8 实际数值

Fig.2

Matching mechanism and process"

Tab.3

Original information and supporting data of orders"

订单
序号		 风格 工艺 月销
量/件		 售价/
元		 O i 1 O i 2 O i 3 O i 4 O i 5
订单1 1 0 1659 269 1 0 3 1700 53.8
订单2 1 1 1040 369 1 1 6 1000 73.8
订单3 1 0 917 229 1 0 3 900 45.8
订单4 1 2 856 369 1 2 6 900 73.8
订单5 2 0 796 229 2 0 3 800 45.8
订单6 1 3 791 399 1 3 7 800 79.8

Tab.4

Supporting data of manufacturers"

制造商
序号		 S j 1 S j 2 S j 3 S j 4 S j 5 S j 6 S j 7 S j 8
制造商1 1,2 0,3 3 0 2 0 900 200
制造商2 1,2 0,1,2,3 8 9 9 9 5 500 700
制造商3 1 0,1,2 6 8 8 6 2 000 200
制造商4 1,2,3 0,2,3 4 2 6 0 2 500 200
制造商5 1,2 1,2 5 6 6 0 1 000 150
制造商6 1 2,3 7 9 8 5 600 600

Tab.5

Ordering utility"

订单
序号		 Uij
制造商1 制造商2 制造商3 制造商4 制造商5 制造商6
订单1 0.20 0.29 0.39 0.14 0.00 0.00
订单2 0.00 0.29 0.39 0.00 0.00 0.00
订单3 0.20 0.29 0.39 0.14 0.00 0.00
订单4 0.00 0.29 0.39 0.00 0.00 0.47
订单5 0.33 0.43 0.00 0.26 0.00 0.00
订单6 0.00 0.29 0.00 0.00 0.00 0.47

Tab.6

Order receiving utility"

制造商
序号		 Gji
制造商1 制造商2 制造商3 制造商4 制造商5 制造商6
制造商1 0 0 41 220 66 420 36 640 63 840
制造商2 91 460 73 800 41 220 66 420 36 640 63 840
制造商3 91 460 73 800 41 220 66 420 36 640 63 840
制造商4 91 460 73 800 41 220 66 420 36 640 63 840
制造商5 0 73 800 41 220 66 420 36 640 63 840
制造商6 0 0 0 0 0 0

Tab.7

Stable matching process and matching results"

项目 各制造商/订单序号
1 2 3 4 5 6
制造商对订单的偏好排序 P ( S j ) {4,6,3,5} {1,2,4,6,3,5} {1,2,4,6,3,5} {1,2,4,6,3,5} {2,4,6,3,5} {}
订单对制造商的偏好排序P ( O i ) {3,2,1,4} {3,2} {3,2,1,4} {6,3,2} {2,1,4} {6,2}
第1轮订单邀约制造商 S3 S3 S3 S6 S2 S6
第1轮制造商决策 A R R R A R
第1轮后决策结果 (O1, S3) Num Num Num (O5, S2) Num
第2轮订单邀约制造商 S2 S2 S3 S2
第2轮制造商决策 A A R A
第2轮后决策结果 (O1, S3) (O2, S2) (O3, S2) Num (O6, S2)
第3轮订单邀约制造商 S2
第3轮制造商决策 A
第3轮后决策结果 (O1, S3) (O2, S2) (O3, S2) (O4, S2) (O6, S2)
最终订单匹配集合M (O1, S3) (O2, S2) (O3, S2) (O4, S2) (O5, S2) (O6, S2)
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