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Published in: Neural Computing and Applications 2/2014

01-08-2014 | Original Article

A fuzzy system approach to multilateral automated negotiation in B2C e-commerce

Authors: Bahador Shojaiemehr, Marjan Kuchaki Rafsanjani

Published in: Neural Computing and Applications | Issue 2/2014

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Abstract

Software agents in e-commerce systems are assigned to the participants. Buyer and supplier agents into multi-agent system architecture of the e-commerce system negotiate with others through an automated negotiation mechanism. In this study, an automated negotiation to interact between buyer and supplier and attain agreement for both is presented. A fuzzy inference system was used to automate negotiation process and consider two effective factors in the negotiation process: requirements and preferences. Requirements are qualitative or quantitative values which the participants assign to the issues of negotiation. Preferences of the participants are priorities assigned by them to issues. These values express an importance measure of issues from a participant perspective. Proposed model applies different fuzzy inference system (FIS) schemes for qualitative and quantitative negotiation issues to enhance the satisfaction level of the buyer and supplier. The FISs infer based on the preferences and requirements of both parties. Additionally, analytic hierarchy process was used to get preferences of the issues. In this proposal, mediator uses issue trade-offs strategy in which multiple issues are traded-offs against one another. The model applies a fuzzy system approach to make trade-offs.

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Metadata
Title
A fuzzy system approach to multilateral automated negotiation in B2C e-commerce
Authors
Bahador Shojaiemehr
Marjan Kuchaki Rafsanjani
Publication date
01-08-2014
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 2/2014
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-013-1491-y

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