|
|
|
| Evaluating and Optimizing Supply Chains with LMBP Algorithm |
Meng Hu1,2, Liang Xiaobei1, Yang Yixiong2,3, Li Min2,3( ) |
1School of Economics and Management, Tongji University, Shanghai 200092, China
2College of Fashion and Design, Donghua University, Shanghai 200051, China
3Shanghai Institute of Design and Innovation, Tongji University, Shanghai 200092, China |
|
|
|
|
Abstract [Objective] This paper uses the LMBP algorithm of feedback neural network to evaluate and optimize the supply chains, aiming to improve the decision-making of enterprises. [Methods] First, we built an evaluation model for supply chains. Then, we generated 21 indicators for corporate performance based on this model. Third, we used the MATLAB to evaluate this algorithm. [Results] The proposed method helped enterprises obtain the results of performance analysis in time, and then improved the management of procurement, inventory, and sales. It reduced the operation costs of enterprises, and improved the decision making process. [Limitations] The new method should be examined with more cases. [Conclusions] The proposed method could improve the performance of supply chains.
|
|
Received: 26 July 2018
Published: 11 December 2018
|
|
|
| [1] |
赵睿. 工业4.0时代商业大数据技术智能供应链的模式研究[J]. 商业经济研究, 2018(6): 30-33.
|
| [1] |
(Zhao Rui.Research on the Mode of Intelligent Supply Chain of Commercial Big Data Technology in Industrial 4 Era[J]. Journal of Commercial Economics, 2018(6): 30-33.)
|
| [2] |
Barton D, Court D.Making Advanced Analytics Work for You[J]. Harvard Business Review, 2012, 90(10): 78-83.
doi: 10.1007/s11213-012-9233-0
pmid: 23074867
|
| [3] |
Chen H, Chiang R H L, Storey V C. Special Issue: Business Intelligence and Analytics: From Big Data to Big Impact[J]. MIS Quarterly, 2013, 36(4): 1165-1188.
|
| [4] |
Ozer M.Understanding the Impacts of Product Knowledge and Product Type on the Accuracy of Intentions-based New Product Predictions[J]. European Journal of Operational Research, 2011, 211(2): 359-369.
doi: 10.1016/j.ejor.2010.12.012
|
| [5] |
李国刚, 宫小平. 大数据信息对二级供应链利润的影响与协调研究[J]. 统计与信息论坛, 2018, 33(4): 32-39.
|
| [5] |
(Li Guogang, Gong Xiaoping.Study on the Impact and Coordination of Big Data Information on the Profit of Two-Stage Supply Chain[J]. Statistics & Information Forum, 2018, 33(4): 32-39.)
|
| [6] |
吉峰, 张婷, 巫凡. 大数据能力对传统企业互联网化转型的影响——基于供应链柔性视角[J]. 学术界, 2016(2): 68-78, 326.
doi: 10.3969/j.issn.1002-1698.2016.02.007
|
| [6] |
(Ji Feng, Zhang Ting, Wu Fan.Frame Model for Influence Mechanism from Big Data Capability to Internet-based Transformation of Traditional Enterprise: The Visual Angle of Supply Chain Flexibility[J]. Academics, 2016(2): 68-78, 326.)
doi: 10.3969/j.issn.1002-1698.2016.02.007
|
| [7] |
蒋清泉, 郝鹭捷. 基于快速反应的我国服装业供应链优化研究[J]. 生产力研究, 2014(4): 76-81.
|
| [7] |
(Jiang Qingquan, Hao Lujie.Research on Supply Chain Optimization of China’s Garment Industry Based on Rapid Response[J]. Productivity Research, 2014(4): 76-81.)
|
| [8] |
邵丹, 杨以雄, 张燕, 等. 大卖场服装零售绩效评估模型[J]. 东华大学学报: 自然科学版, 2010, 36(3): 294-299.
doi: 10.3969/j.issn.1671-0444.2010.03.015
|
| [8] |
(Shao Dan, Yang Yixiong, Zhang Yan, et al.Model of Performance Assessment on Garment Retail in Hypermarket[J]. Journal of Donghua University: Natural Science Edition, 2010, 36(3): 294-299.)
doi: 10.3969/j.issn.1671-0444.2010.03.015
|
| [9] |
赵巍. 浅析公司不同发展阶段的KPI指标设计——以NS服装公司销售人员考核为例[J]. 法制与社会, 2010(21): 114.
doi: 10.3969/j.issn.1009-0592.2010.21.074
|
| [9] |
(Zhao Wei.Analysis of KPI Index Design in Different Development Stages of the Company: Case Study of Sales Staff Assessing of Company NS[J]. Legal System and Society, 2010(21): 114.)
doi: 10.3969/j.issn.1009-0592.2010.21.074
|
| [10] |
李敏, 孟虎, 徐思巧. 基于AHP和多目标规划的面料供应商评价选择研究[J]. 北京服装学院学报: 自然科学版, 2017, 37(3): 63-74.
|
| [10] |
(Li Min, Meng Hu, Xu Siqiao.Study on Evaluation and Selection on Fabric Suppliers Based on AHP and Multi-objective Programming[J]. Journal of Beijing Institute of Clothing Technology: Natural Science Edition, 2017,37(3): 63-74.)
|
| [11] |
熊棕瑜. 基于成本管理的服装供应链流程优化研究——以D企业生产供应中心为例[D]. 上海: 东华大学, 2017.
|
| [11] |
(Xiong Zongyu.Study on Optimization of Apparel Supply Chain Process Based on Cost Management——Production Center of Brand D Case Analysis[D]. Shanghai: Donghua University, 2017.)
|
| [12] |
陈炜. 面向服装制造企业的服装供应链风险评估及模型研究[D]. 杭州: 浙江理工大学, 2011.
|
| [12] |
(Chen Wei.Research on the Evaluation and Model of Apparel Supply Chain Risk for Apparel Manufacturing Enterprises[D]. Hangzhou: Zhejiang Sci-Tech University, 2011.)
|
| [13] |
徐慧娟, 杨以雄, 王元明. 基于BSC和AHP的服装产业集群评价模型及案例分析[J]. 东华大学学报: 自然科学版, 2010, 36(3): 300-304.
doi: 10.3969/j.issn.1671-0444.2010.03.016
|
| [13] |
(Xu Huijuan, Yang Yixiong, Wang Yuanming.Apparel Industry Clusters Evaluation Model and Case Analysis Based on BSC and AHP[J]. Journal of Donghua University: Natural Science Edition, 2010, 36(3): 300-304.)
doi: 10.3969/j.issn.1671-0444.2010.03.016
|
| [14] |
Saaty T L.The Analytic Hierarchy Process: Planning, Priority Setting, Resources Allocation[M]. New York: McGraw Hill, 1980: 22-71.
|
| [15] |
郑培. 动态供应链绩效评价方法研究[D]. 长沙: 湖南大学, 2008.
|
| [15] |
(Zheng Pei.Research on the Dynamic Supply Chain Performance Measurement Methods[D]. Changsha: Hunan University, 2008.)
|
| [16] |
张春姣. 服装品牌供应链绩效评价及案例研究[D]. 上海: 东华大学, 2012.
|
| [16] |
(Zhang Chunjiao.The Performance Assessment of Apparel Brand Supply Chain and Case Study[D]. Shanghai: Donghua University, 2012.)
|
| [17] |
于涛. BP网络自适应学习率算法分析[D]. 大连: 大连理工大学, 2011.
|
| [17] |
(Yu Tao.Analysis on Self-adaptive Learning Rate Algorithms for BP Neural Networks[D]. Dalian: Dalian University of Technology, 2011.)
|
| [18] |
Schoenherr T, Speier-Pero C. Data Science, Predictive Analytics,Big Data in Supply Chain Management: Current State and Future Potential[J]. Journal of Business Logistics, 2015, 36(1): 120-132.
doi: 10.1111/jbl.12082
|
| [19] |
Schlegel G L.Utilizing Big Data and Predictive Analytics to Manage Supply Chain Risk[J]. The Journal of Business Forecasting, 2014, 33(4): 11-33.
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
| |
Shared |
|
|
|
|
| |
Discussed |
|
|
|
|
