Name
Abstract | ||
|---|---|---|
Multi-attribute auctions allow negotiations over multiple attributes besides price. Multiple criteria English reverse auction mechanisms differ regarding the aggregation model used to represent the buyer's preferences and the feedback information provided to bidders during the auction. In this paper, we present a unified framework, called MERA in order to integrate existing mechanisms and guide the design of new ones. Framework MERA both provides an automated buyer agent that manages auctions and a formal model that describes an auction mechanism. This model includes a class of preference relations used to express the buyer's preference relation, a class of request relations used to formulate the feedback, and a class of constraints used to express the initial requirements on the purchased item. We study efficiency for multiple criteria English reverse auction processes, and we show that any process derived from framework MERA is efficient. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.3233/WIA-2008-0148 | Web Intelligence and Agent Systems |
Keywords | Field | DocType |
english reverse auction process,auction mechanism,english reverse auction mechanism,multi-attribute auction,unified framework,preference relation,multiple criteria auction mechanism,automated buyer agent,framework mera,aggregation model,multiple criterion,formal model,multiple criteria decision analysis | Computer science,Combinatorial auction,Operations research,Generalized second-price auction,Common value auction,Vickrey–Clarke–Groves auction,Auction theory,Artificial intelligence,Reverse auction,Auction algorithm,Revenue equivalence,Machine learning | Journal |
Volume | Issue | Citations |
6 | 4 | 13 |
PageRank | References | Authors |
0.64 | 18 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marie-jo Bellosta | 1 | 84 | 56.39 |
| Sylvie Kornman | 2 | 47 | 3.61 |
| Daniel Vanderpooten | 3 | 1153 | 74.66 |