A Framework for Online Reverse Auction Based on Market Maker Learning with a Risk-Averse Buyer
Joint Authors
Tayaran, Hojat
Ghazanfari, Mehdi
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-06
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
The online reverse auction is considered as a new e-commerce approach to purchasing and procuring goods and materials in the supply chain.
With the rapid and ever-expanding development of information technology as well as the increasing usage of the Internet around the world, the use of an online reverse auction method to provide the required items by organizations has increased.
Accordingly, in this paper, a new framework for the online reverse auction process is provided that takes both sides of the procurement process, namely, buyer and seller.
The proposed process is a multiattribute semisealed multiround online reverse auction.
The main feature of the proposed process is that an online market maker facilitates the seller’s bidding process by the estimation of the buyer’s scoring function.
For this purpose, a multilayer perceptron neural network was used to estimate the scoring function.
In this case, in addition to hiding the buyer’s scoring function, sellers can improve their bids using the estimated scoring function and a nonlinear multiobjective optimization model.
The NSGA II algorithm has been used to solve the seller model.
To evaluate the proposed model, the auction process is simulated by considering three scoring functions (additive, multiplicative, and risk-aversion) and two types of open and semisealed auctions.
The simulation results show that the efficiency of the proposed model is not significantly different from the open auction, and in addition, unlike the open auction, the buyer information was not disclosed.
American Psychological Association (APA)
Tayaran, Hojat& Ghazanfari, Mehdi. 2020. A Framework for Online Reverse Auction Based on Market Maker Learning with a Risk-Averse Buyer. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1196062
Modern Language Association (MLA)
Tayaran, Hojat& Ghazanfari, Mehdi. A Framework for Online Reverse Auction Based on Market Maker Learning with a Risk-Averse Buyer. Mathematical Problems in Engineering No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1196062
American Medical Association (AMA)
Tayaran, Hojat& Ghazanfari, Mehdi. A Framework for Online Reverse Auction Based on Market Maker Learning with a Risk-Averse Buyer. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1196062
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1196062