Abstract
Recently there has been a surge of interest in auctions research triggered on the one hand by auctions of bandwidth and other public assets and on the other by the popularity of Internet auctions and the possibility of new auction formats enabled by e-commerce. Simultaneous auction of items is a popular auction format. We consider the problem of maximizing total revenue in the simultaneous auction of a set of items where the bidders have individual budget constraints. Each bidder is permitted to bid on all the items of his choice and specifies his budget constraint to the auctioneer, who must select bids to maximize the revenue while ensuring that no budget constraints are violated. We show that the problem of maximizing revenue is such a setting is NP-hard, and present a factor-1.62 approximation algorithm for it. We formulate the problem as an integer program and solve a linear relaxation to obtain a fractional optimal solution, which is then deterministically rounded to obtain an integer solution. We argue that the loss in revenue incurred by the rounding procedure is bounded by a factor of 1.62.
Vijay Kumar can be reached at amazon.com, 605 5th Avenue South, Seattle, WA 98104, USA. E-mail: vijayk@amazon.com
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© 2001 Springer-Verlag Berlin Heidelberg
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Garg, R., Kumar, V., Pandit, V. (2001). Approximation Algorithms for Budget-Constrained Auctions. In: Goemans, M., Jansen, K., Rolim, J.D.P., Trevisan, L. (eds) Approximation, Randomization, and Combinatorial Optimization: Algorithms and Techniques. RANDOM APPROX 2001 2001. Lecture Notes in Computer Science, vol 2129. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44666-4_14
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DOI: https://doi.org/10.1007/3-540-44666-4_14
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