A supplier offer modification approach based on fuzzy systems for automated negotiation in e-commerce
In E-commerce, numbers of transactions are increasing day by day in B2B and B2C trade. Online negotiation is possible because of automated negotiation. Autonomous entities such as agents could help in these situations. Providing an offer which has maximum utilities for both trading parties into possible shortest time is the main aim of this work. Proposed model applies issue trade-offs strategy in which multiple issues are traded-offs against one another to maximize participant satisfaction. To make trade-offs the model applies a fuzzy system approach. The automated negotiation model in this article has a process without offer generating and exchanging between buyer and supplier agents to explore time-consuming negotiation process in earlier researches. Mediator component searches an optimal offer that satisfies buyer and supplier requirements. The system will utilize fuzzy inference systems to automate negotiation process and considers two effective factors in the negotiation process: requirements and preferences. Requirements are qualitative or quantitative values which the participants assign to issues for negotiation. Preferences of the participants are priorities assigned to the issues. These values express an importance measure of the issues from a participant perspective. Analytic hierarchy process (AHP) is used to get preferences of the issues. Proposed model applies different Fuzzy Inference System (FIS) schemes for qualitative and quantitative negotiation issues to enhance the satisfaction level of buyers and suppliers. Experimental results show that how the model fulfills the main aim of our work.