A Reinforcement Learning Approach for Price Offer in Supplier Selection Process

被引:0
作者
Derhami, Vali [1 ]
Saadatjoo, Mohammad Ali [2 ]
Saadatjoo, Fatemeh [3 ]
机构
[1] Yazd Univ, Dept Elect & Comp Engn, Yazd, Iran
[2] Islamic Azad Univ Qazvin, Dept Informat Technol, Qazvin, Iran
[3] Yazd ACECR Higher Educ Inst, Dept Comp, Yazd, Iran
来源
INFORMATION AND COMMUNICATION TECHNOLOGIES | 2010年 / 101卷
关键词
Supplier selection process; Reinforcement learning; Price-offer; TO-ORDER ENVIRONMENT; NEURAL-NETWORKS; NEGOTIATION; MODEL;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Supplier selection negotiation is a challenged, complex, and nondeterministic problem. To solve the problem well, it is necessary to develop an intelligent system for negotiation support in supplier selection process. Reinforcement Learning (RL) is a powerful algorithm which can be used for the price offer in supplier selection negotiation with the aim of maximizing the demander's profits. In this paper, we formulate the supplier selection as a RL problem. States, actions, and reinforcement function are defined in this problem. In the next step, we compare the proposed RL method with traditional method.
引用
收藏
页码:326 / +
页数:3
相关论文
共 7 条