Negotiation Model Based on Uncertainty Multi-attribute Decision Making

摘要：

The problem for uncertainty of information on the multi-attribute which exists in the e-commerce negotiation model, it is easy to describe but difficult to achieve an optimal solution owing to the high computational complexity. In order to yield a top-quality deal and shorten the negotiation period, we propose an UEOWA decision making operator based on the application of vague mathematics to evaluate negotiators preference for different attribute. An algorithm combining fuzzy membership with Bayesian learning mechanism is developed, which solves the concession problem during the process of multi-attribute negotiations. The experiment demonstrated that the model ensures the participants can reach a mutually beneficial agreement in a short time. The computational study showed that the proposed algorithm is a feasible and effective approach for uncertainty of information on the multi-attribute negotiation problem.

关键词： Uncertainty Decision Making Operator Fuzzy Membership Bayesian Learning Mechanism Negotiation Model

作者: Chen Pei-you Li Yi-ling

作者单位: College of Economic and Management, Heilongjiang Institute of Science and Technology, Harbin 150027, China

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 1553-1556

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）