Frugal Auction Design for Set Systems: Vertex Cover and Knapsack

被引:3
|
作者
Hajiaghay, Mohammadtaghi [1 ]
Khani, Mohammad Reza [2 ]
Seddighin, Saeed [1 ]
机构
[1] Univ Maryland, College Pk, MD 20742 USA
[2] Microsoft R&D, Bellevue, WA USA
关键词
Frugal; Knapsack; Vertex Cover; PROCUREMENT AUCTION;
D O I
10.1145/3219166.3219229
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
We study mechanism design for procurement auctions in which the goal is to buy a subset of items or hire a team of providers. In order to measure the efficiency of a mechanism, one defines an appropriate benchmark which denotes a reasonable expectation of the payments and defines the overpayment of a mechanism based on the benchmark. This ratio is called the frugality ratio of the mechanism. Procurement auctions are well-studied and benchmarks proposed for these auctions have evolved over a sequence of papers [2, 5, 8, 12, 13]. In this work, we introduce a newer benchmark, and based on that, study classic procurement auctions. Our benchmark addresses critical issues raised by the unintuitive behavior of the previous benchmarks. We show two attractive properties for our benchmark which have been lacking in the previous proposals: monotonicity and smoothness. Based on our benchmark, we provide positive results for vertex cover and knapsack auctions. Prior to this work, Kempe et al. [13] propose a constant approximation mechanism for vertex cover auctions. However, their analysis suffers from an error. We give a correct analysis to the mechanism of Kempe et al. [13] with respect to our benchmark. In particular, we prove their mechanism is optimal up to a constant factor. Our analysis is different from what Kempe et al. [13] propose. We also study the knapsack auctions and give a truthful mechanism for such auctions with a bounded frugality ratio. We show that this is almost tight by presenting a lower bound on the frugality ratio of any truthful mechanism for such auctions. All our results depend on both properties of the benchmark. (1)
引用
收藏
页码:645 / 662
页数:18
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