A Support Vector Machines Based framework of Inventory Decision Supporting System

摘要：

Inventory Decision Supporting System (IDSS) is one of the most hot points in Logistics, since the inventory decision is conditioned by so many changing factors, available models and methods seem not so effective as in image. A new framework of Inventory Decision Supporting System is provided in this paper. The framework is based on pattern classification. The classification adopts Support Vector Machines, which is more suitable for context of fewer samples and more factors for consideration. Our IDSS dynamically evaluates the efficiency of models and its applicable targets to adjusts decision to adapt changing conditions.

关键词： inventory decision supporting system pattern classification efficiency evaluation support vector machines

作者: Li Qingsong Qin Lizhi

作者单位: School of Transportation and Automotive Engineering,Xihua University Chengdu, China

会议类型: 国际会议

会议名称: 2010 IEEE International Conference on Advanced Management Science(2010年IEEE高级管理科学国际会 IEEE ICAMS 2010)

会议地点: 成都

会议语种:英文

页码: 576-578

在线出版日期: 2010-07-09（万方平台首次上网日期，不代表论文的发表时间）