A Multi-Criteria Reverse Auction to Support Public Purchasing in Brazil

In this paper, we propose a Multi-Criteria Reverse Auction (MCRA) approach based on the Composition of Probabilistic Preferences (CPP) multi-criteria method. In CPP method, the evaluations of alternatives in each criterion are converted into possible values by using a triangular distribution, allowing imprecision to be considered. The evaluations of the alternatives in each criterion are converted into a vector of probabilities of each alternative being the best (or the worst) in the criterion. Then, the measure of preference for any alternative, considering all the criteria, is given by the composition of its respective probabilities, not being necessary to provide intercriteria information, which is an advantage of this method over the others multi-criteria methods regarding its applicability to real life-problems. The MCRA approach was structured to support Brazilian public reverse auctions. An example of application was performed to demonstrate its applicability, demonstrating that the proposed approach can be easily incorporated into the Brazilian public reverse auctions. The MCRA approach improves the quality of public purchasing decision by assuring the consideration of multiple criteria in the evaluation phase and providing better results for both parties (buyer and sellers).