Membership function based matching approach of buyers and sellers through a broker in open e-marketplace

A broker in a market enables buyers and sellers to do business with each other and can provide many value-adding functions that cannot be replaced by direct buyer-seller dealings. Recently, some research has focused on this issue. However, broker modelling based on buyer¿s membership functions to carry out a matching process between buyer¿s requirements in fuzzy preference information and seller¿s offers is still sparse. Thus, this paper proposes membership function based matching approach of buyers and sellers through a broker in open e-marketplace. The major contributions of this paper are that (i) a proposed framework is applicable to help a broker to carry out the matching process between buyers and sellers; (ii) a proposed method is to determine buyer¿s attribute weight with soft constraints by using association rule mining; and (iii) an objective optimization function and a set of constraints are built to help a broker to maximize buyer¿s total utility. Experimental results demonstrate the good performance of the proposed approach in terms of satisfying buyer¿s requirements and maximizing buyer¿s total utility.