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.