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

Journal Article


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Abstract


  • 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.

Publication Date


  • 2017

Citation


  • Le, D., Zhang, M. & Ren, F. (2017). Membership function based matching approach of buyers and sellers through a broker in open e-marketplace. Studies in Computational Intelligence, 670 125-137. Studies in Computational Intelligence

Scopus Eid


  • 2-s2.0-84997820994

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=7514&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/6484

Number Of Pages


  • 12

Start Page


  • 125

End Page


  • 137

Volume


  • 670

Place Of Publication


  • Germany

Abstract


  • 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.

Publication Date


  • 2017

Citation


  • Le, D., Zhang, M. & Ren, F. (2017). Membership function based matching approach of buyers and sellers through a broker in open e-marketplace. Studies in Computational Intelligence, 670 125-137. Studies in Computational Intelligence

Scopus Eid


  • 2-s2.0-84997820994

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=7514&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/6484

Number Of Pages


  • 12

Start Page


  • 125

End Page


  • 137

Volume


  • 670

Place Of Publication


  • Germany