Pricing ordered items
Pricing ordered items
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为订购的商品定价
DOI:
10.1145/3519935.3520065
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发表时间:
2022
期刊:
影响因子:
--
通讯作者:
Tzamos, Christos
中科院分区:
文献类型:
--
作者:
Chawla, Shuchi;Rezvan, Rojin;Teng, Yifeng;Tzamos, Christos
We study the revenue guarantees and approximability of item pricing. Recent work shows that withnheterogeneous items, item-pricing guarantees anO(logn) approximation to the optimal revenue achievable by any (buy-many) mechanism, even when buyers have arbitrarily combinatorial valuations. However, finding good item prices is challenging – it is known that even under unit-demand valuations, it is NP-hard to find item prices that approximate the revenue of the optimal item pricing better thanO(√n).Our work provides a more fine-grained analysis of the revenue guarantees and computational complexity in terms of the number of item “categories” which may be significantly fewer thann. We assume the items are partitioned inkcategories so that items within a category are totally-ordered and a buyer’s value for a bundle depends only on the best item contained from every category.We show that item-pricing guarantees anO(logk) approximation to the optimal (buy-many) revenue and provide a PTAS for computing the optimal item-pricing whenkis constant. We also provide a matching lower bound showing that the problem is (strongly) NP-hard even whenk=1. Our results naturally extend to the case where items are only partially ordered, in which case the revenue guarantees and computational complexity depend on the width of the partial ordering, i.e. the largest set for which no two items are comparable.
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DOI:
--
发表时间:
2013
影响因子:
11.1
作者:
Xinye Li;A. Yao
通讯作者:
A. Yao
DOI:
--
发表时间:
2020
期刊:
IEEE Annual Symposium on Foundations of Computer Science
影响因子:
--
作者:
Paul Dütting;Thomas Kesselheim;Brendan Lucier
通讯作者:
Brendan Lucier
DOI:
--
发表时间:
2011
期刊:
IEEE Annual Symposium on Foundations of Computer Science
影响因子:
--
作者:
Yang Cai;C. Daskalakis
通讯作者:
C. Daskalakis
DOI:
--
发表时间:
2009
期刊:
International Workshop and International Workshop on Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques
影响因子:
--
作者:
R. Khandekar;T. Kimbrel;K. Makarychev;M. Sviridenko
通讯作者:
M. Sviridenko
影响因子:
1.3
作者:
ROCHET, JC
通讯作者:
ROCHET, JC