Solving a multi-attribute reverse auction problem by fuzzy data envelopment analysis method

The development of internet technologies makes the multi-attribute reverse auction to be a powerful tool in the business to business sector for lowering transaction costs and improving supply chain management capabilities. The multiattribute reverse auction has important significance in items procurement. In this paper, the fuzzy data envelopment analysis (DEA) models of multi-attribute reverse auction are presented for the buyer to select the best suppliers. By the use of fuzzy number, the attributes with uncertain or inaccurate data can be described properly. In view of the characters of fuzzy number, the corresponding ranking method of the efficiencies of suppliers is developed since the results of fuzzy data envelopment analysis models are fuzzy numbers. The use of DEA models overcomes the difficult of determination of score or valuation function of the buyer in usual multi-attribute auction process. Specifically, the proposed model with multiple winners is also suitable for the multi-unit multi-attribute reverse auction. The validity of the proposed approach is demonstrated through the number illustrative examples. Computational results indicate the feasibility of the proposed method.