A Multi-attribute Auction Model by Dominance-based Rough Sets Approach

Rong Zhang, Bin Liu, Sifeng Liu

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 multi- attribute 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.