A multi-attribute auction model by dominance based rough sets approach
Author(s) -
Rong Zhang,
Liu Bin,
Sifeng Liu
Publication year - 2010
Publication title -
computer science and information systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.244
H-Index - 24
eISSN - 2406-1018
pISSN - 1820-0214
DOI - 10.2298/csis090804025r
Subject(s) - computer science , auction theory , revenue equivalence , auction algorithm , rough set , vickrey–clarke–groves auction , preference , simplicity , data mining , operations research , common value auction , microeconomics , mathematics , economics , philosophy , epistemology
As an alternative to the price-based traditional auction model, the multi-attribute auction model is an integrated model requiring the simultaneous trade of different types of attributes as the sellers and buyers deal. As a result, the design and modeling of the auction mechanism have become very difficult. This paper proposes a multiattribute auction model using the dominance-based rough sets approach (DRSA). The multi-attribute decision method by DRSA can directly mine out the preference relations between the attributes of alternatives so that relevant auction mechanisms can be designed. This model uses a natural reasoning procedure similar to that of decision makers. Finally, a numerical example demonstrates the simplicity, efficiency, and feasibility of the proposed auction model.
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