Bayesian network forecasting of key material supply in uncertain environment
Supply chain increase in complexity, forecast of key material supply has become indispensable to effective operations management in global market Unfortunately, rapid technological changes and an abundance of product configurations mean that the supply for key material is frequently volatile and hard to forecast The paper describes a Bayesian Network (BN) model which was embodies a parametric description of some factors in key material supply forecasting, such as life cycle, oil price, salary level, BOM, supplydemand relationship, and seasonal fluctuations, etc. Furthermore, the model is able to pool supply patterns with little or no supply history data. Finally, the paper discusses the problem addressed by the model, and then analyses its forecast performance.
Bayesian Network supply forecasting uncertain evironment supply chain
JIA Jiangming BAO Zhigang DONG Baoli ZHU Kaisheng
Faculty of Mechanical Engineering & Automation Zhejiang Sci-Tech University Hangzhou 310018 China Yiwu Xinhong Zipper Co., Ltd. Yiwu 312000 China
国际会议
杭州
英文
81-85
2010-10-21（万方平台首次上网日期，不代表论文的发表时间）