面向服装供应链平台的订单生产双向推荐策略

doi:10.13475/j.fzxb.20210507606

Abstract

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

CHEN Qingting, DU Jinsong, LIN Xiang, ZHU Jianlong. A duo-directional recommendation strategy for order-production oriented to apparel supply chain platforms[J].Journal of Textile Research, 2022, 43(06): 151-156.

Figures/Tables 9

Fig.1

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 $Y j i 1$	—	—
	可生产性 $N j i 1$	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.1

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

Tab.2

Fig.2

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.3

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.4

Tab.5

Tab.6

Tab.7

Stable matching process and matching results"

项目	各制造商/订单序号
项目	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)

Tab.7

References 10

[1]	SIMEONE A, ZENG Y, CAGGIANO A. Intelligent decision-making support system for manufacturing solution recommendation in a cloud framework[J]. The International Journal of Advanced Manufacturing Technology, 2021(112):1035-1050.
[2]	谢雪妍. 生产外包下的服装企业订单分配优化研究[J]. 物流技术与应用, 2020, 25(3): 135-138.
	XIE Xueyan. Research on order allocation optimization of clothing enterprise with production outsourcing[J]. Logistics & Material Handling, 2020, 25(3): 135-138.
[3]	黄辉, 纪玉娇, 杨冬辉, 等. 产能约束下多源制造商选择及订单分配研究[J]. 工业工程与管理, 2018, 23(4): 120-128.
	HUANG Hui, JI Yujiao, YANG Donghui, et al. Research on multiple supplier selection and order distribution under capacity constraints[J]. Industrial Engineering & Management, 2018, 23(4):120-128.
[4]	PASQUALE V D, NENNI M E, RIEMMA S. Order allocation in purchasing management: a review of state-of-the-art studies from a supply chain perspective[J]. International Journal of Production Research, 2020, 58(15): 4741-4766. doi: 10.1080/00207543.2020.1751338
[5]	GUO S, DONG M. Order matching mechanism of the production intermediation internet platform between retailers and manufacturers[J]. The International Journal of Advanced Manufacturing Technology, 2020, 115(3):949-962. doi: 10.1007/s00170-020-06175-z
[6]	张青山, 刘岩峰, 徐伟. 多重不确定性需求下多产品订单相似性研究[J]. 沈阳工业大学学报(社会科学版), 2020, 13(3): 219-225.
	ZHANG Qingshan, LIU Yanfeng, XU Wei. Research on similarity of multi-variety product orders with multiple uncertainties in demand[J]. Journal of Shenyang University of Technology(Social Science Edition), 2020, 13(3):219-225.
[7]	张于贤, 丁修坤. 面向多品种小批量的订单成组模型研究[J]. 系统科学学报, 2018, 26(1): 92-95.
	ZHANG Yuxian, DING Xiukun. An order group model for muti-varieties and small batch[J]. Chinese Journal of Systems Science, 2018, 26(1): 92-95.
[8]	周兴建, 戴金山, 姜文可. 云制造模式下基于双目标的供应链订单生产规划优化[J/OL]. 武汉大学学报(理学版), 2020.DOI: 10.14188/j.1671-8836.2020.0272. doi: 10.14188/j.1671-8836.2020.0272
	ZHOU Xingjian, DAI Jinshan, JIANG Wenke. Optimization of supply chain order production planning based on bi-objective under the cloud manufacturing mode[J/OL]. Journal of Wuhan University(Natural Science Edition),2020.DOI: 10.14188/j.1671-8836.2020.0272. doi: 10.14188/j.1671-8836.2020.0272
[9]	BEHDIN V N, REZA T M, ZDENěK H, et al. Incorporating order acceptance, pricing and equity considerations in the scheduling of cloud manufacturing systems: matheuristic methods[J]. International Journal of Production Research, 2021, 59(7):2009-2027. doi: 10.1080/00207543.2020.1806370
[10]	杜劲松, 余雅芸, 赵妮, 等. 不同类型服装企业智能制造能力成熟度评价模型[J]. 纺织学报, 2021, 42(5):162-167.
	DU Jinsong, YU Yayun, ZHAO Ni, et al. Evaluation modelling for maturity in intelligent manufacturing for multi-type clothing factories[J]. Journal of Textile Research, 2021, 42(5):162-167.

Related Articles 15

[1]	. Bidirectional recommendation strategy for order production oriented to apparel supply chain platform [J]. , 0, (): 0-0.
[2]	ZHANG Yaqi, LI Xiaohui. Prediction method of human skin deformation variables for joint position during exercise [J]. Journal of Textile Research, 2022, 43(06): 140-144.
[3]	MA Liang, LI Jun. Application progress in cold protective clothing based on multiple intelligent technologies [J]. Journal of Textile Research, 2022, 43(06): 206-214.
[4]	ZHANG Jian, XU Kaiyi, ZHAO Songling, GU Bingfei. Classification and recognition of young males' neck-shoulder shape based on 2-D photos [J]. Journal of Textile Research, 2022, 43(05): 143-149.
[5]	JIN Jindi, YAO Tong, WANG Jun, SUN Jianmei, PAN Li. Study on somatotype classification of elderly women in Dalian area [J]. Journal of Textile Research, 2022, 43(05): 150-155.
[6]	PAN Jiahao, ZHOU Qihong, CEN Junhao, LI Shujia, ZHOU Shenhua. Optimization modeling for packaging order allocation for garment enterprises and solution finding using non-dominated genetic algorithm [J]. Journal of Textile Research, 2022, 43(05): 156-162.
[7]	WANG Jianping, MIAO Mingzhu, SHEN Deyao, YAO Xiaofeng. Development and performance evaluation of knitted fabric with bionic bird feather structure [J]. Journal of Textile Research, 2022, 43(04): 55-61.
[8]	LEI Ge, LI Xiaohui. Review of digital pattern-making technology in garment production [J]. Journal of Textile Research, 2022, 43(04): 203-209.
[9]	ZHU Xiaorong, HE Jiazhen, WANG Min. Application research progress in phase change materials for thermal protective clothing [J]. Journal of Textile Research, 2022, 43(04): 194-202.
[10]	ZHENG Lu, YAN Weixiong, HU Jueliang, HAN Shuguang. Balanced optimization of garment hybrid assembly line based on modularization [J]. Journal of Textile Research, 2022, 43(04): 140-146.
[11]	QIAN Jing, ZHAO Mengmeng, DANG Tianhua. Quantitative study of air layer under multi-opening air ventilation clothing [J]. Journal of Textile Research, 2022, 43(04): 133-139.
[12]	YU Yukun, SUN Yue, HOU Jue, LIU Zheng, YICK Kitlun. Dynamic finite element modeling and simulation of single layer clothing ease allowance [J]. Journal of Textile Research, 2022, 43(04): 124-132.
[13]	XIA Ming, LI Peiru, DING Rong. Cost rapid accounting technology of dress based on element matching [J]. Journal of Textile Research, 2022, 43(03): 146-152.
[14]	WANG Chunru, YUAN Yue, CAO Xiaomeng, FAN Yilin, ZHONG Anhua. Influence of structural parameters of stand collar on clothing styling [J]. Journal of Textile Research, 2022, 43(03): 153-159.
[15]	JIANG Gaoming, ZHOU Mengmeng, ZHENG Baoping, ZHENG Peixiao, LIU Haisang. Research progress of green and low-carbon knitting technology [J]. Journal of Textile Research, 2022, 43(01): 67-73.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

Comments

Recommended 0

No Suggested Reading articles found!

订单序号	U_ij
订单序号	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

制造商序号	G_ji
制造商序号	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

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

RichHTML

PDF (PC)