STUDY ON THE METHOD OF ORDER OPTIMIZATION AND ARRANGEMENT BASED ON NEURAL NETWORK TECHNOLOGY

被引：0
|
作者：
Wang, Xiao-Feng [1 ,2 ]
Liu, Bin [3 ]
机构：
[1] Beijing Inst Technol, Sch Management & Econ, Beijing 100081, Peoples R China
[2] Hebei Univ Sci & Technol, Acad Affairs Dept, Shijiazhuang 050018, Peoples R China
[3] Hebei Univ Sci & Technol, Coll Econ & Management, Shijiazhuang 050018, Peoples R China
来源：
PROCEEDINGS OF 2009 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-6 | 2009年
关键词：
RBF neural network; order production priority; supply chain; index system;
D O I：
10.1109/ICMLC.2009.5212657
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In the setting of supply chain, order evaluation of the core manufacture enterprise is a task of demand management and the prerequisite for production planning. Order selection is a multi-attribute issue which involves integrated decision-making. In this paper, firstly, an order priority evaluation index system is constructed within a more systematic and comprehensive supply chain setting. Secondly, a model is set up by means of neural network. Thirdly, Matlab is applied to assist design and optimize network. Finally, an empirical research is carried out to compare and analyze the effects of three different decision-making methods. Study shows this approach is valid and practicable.
引用
收藏
页码：2697 / +
页数：2
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