Agile forecasting of dynamic logistics demand

作者：Miao Xin^*; Xi Bao

来源：Transport, 2008, 23(1): 26-30.

DOI：10.3846/1648-4142.2008.23.26-30

• logistics
• forecasting
• supply chain management
• dynamic influencing factors
• agility
• hybrid algorithm
• Swarm
• computer simulation

The objective of this paper is to study the quantitative forecasting method for agile forecasting of logistics demand in dynamic supply chain environment. Characteristics of dynamic logistics demand and relative forecasting methods are analyzed. In order to enhance the forecasting efficiency and precision, extended Kalman Filter is applied to training artificial neural network, which serves as the agile forecasting algorithm. Some dynamic influencing factors are taken into consideration and further quantified in agile forecasting. Swarm simulation is used to demonstrate the forecasting results. Comparison analysis shows that the forecasting method has better reliability for agile forecasting of dynamic logistics demand.

• 出版日期2008
• 单位哈尔滨工业大学