Negotiation model based on uncertainty multi-attribute decision making

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.