Randomized algorithms
Online computation and competitive analysis
Online computation and competitive analysis
Competitive auctions and digital goods
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Truth revelation in approximately efficient combinatorial auctions
Journal of the ACM (JACM)
An approximate truthful mechanism for combinatorial auctions with single parameter agents
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Competitive Auctions for Multiple Digital Goods
ESA '01 Proceedings of the 9th Annual European Symposium on Algorithms
Auction mechanism for optimally trading off revenue and efficiency
Proceedings of the 4th ACM conference on Electronic commerce
Incentive compatible multi unit combinatorial auctions
Proceedings of the 9th conference on Theoretical aspects of rationality and knowledge
Approximation techniques for utilitarian mechanism design
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
On profit-maximizing envy-free pricing
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
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This work obtains truthful mechanisms that aim at maximizing both the revenue and the economic efficiency (social welfare) of unit-demand auctions. In a unit-demand auction a set of k items is auctioned to a set of n consumers, and although each consumer bids on all items, no consumer can purchase more than one item. We present a framework for devising polynomial-time randomized truthful mechanisms that are based on a new variant of the Vickrey-Clarke-Groves (VCG) mechanism. Instead of using reserve prices, this variant of VCG uses the number of objects that we wish to sell as a parameter. Our mechanisms differ in their selection of the number of items to be sold, and allow an interesting trade-off between revenue and economic efficiency, while improving upon the state-of-the-art results for the Unit-Demand Auctions problem (Guruswami et. al.[SODA 2005]). Our probabilistic results depend on what we call the competitiveness of the auction, i.e., the minimum number of items that need to be sold in order to obtain a certain fraction of the maximum efficiency. We denote by ${\mathcal T}$ the optimal efficiency achieved by the VCG mechanism. Our efficiency-oriented mechanism achieves $\Omega{(\mathcal T)}$ efficiency and $\Omega({\mathcal T}/ln(min\{k,n\})$ revenue with probability that grows with the competitiveness of the auction. We also show that no truthful mechanism can obtain an $\omega({\mathcal T}/ln(min\{k,n\})$ expected revenue on every set of bids. In fact, the revenue-oriented mechanism we present achieves $\Omega({\mathcal T}/ln(min\{k,n\})$ efficiency and $\Omega({\mathcal T}/ln(min\{k,n\})$ revenue, but the revenue can actually be much higher, even as large as $\Omega({\mathcal T})$ for some bid distributions.