Truthful Multi-Parameter Auctions with Online Supply: an Impossible Combination

  title={Truthful Multi-Parameter Auctions with Online Supply: an Impossible Combination},
  author={Nikhil R. Devanur and Balasubramanian Sivan and Vasilis Syrgkanis},
We study a basic auction design problem with online supply. There are two unit-demand bidders and two types of items. The first item type will arrive first for sure, and the second item type may or may not arrive. The auctioneer has to decide the allocation of an item immediately after each item arrives, but is allowed to compute payments after knowing how many items arrived. For this problem we show that there is no deterministic truthful and individually rational mechanism that, even with… 
Mechanism Design for Combinatorial Allocation Problems without Quasilinear Utilities
This work analyzes a course allocation problem where students have preferences over schedules and reports on a large-scale course assignment application at the TU Munich, and studies non-quasilinear utility functions as they have been reported for display ad auctions, and proposes a truthful randomized approximation mechanism.
SIGACT News Online Algorithms Column 34: 2018 in review
In this column, I will discuss some papers in online algorithms that appeared in 2018, and have made a selection.


Multi-unit auctions with unknown supply
This work uses a 1<over>4 -competitive algorithm for computing the optimal single price auction assuming that all the agents report their bids truthfully to develop a truthful auction with a constant competitive ratio compared to the optimum offline single-price auction.
Prompt Mechanisms for Online Auctions
Two prompt mechanisms are presented, one deterministic and the other randomized, that guarantee a constant competitive ratio and are presented as a guide to truthful mechanisms that maximize the welfare, the sum of the utilities of winning bidders.
Adaptive limited-supply online auctions
A limited-supply online auction problem, in which an auctioneer has k goods to sell and bidders arrive and depart dynamically, is studied and strategyproof mechanisms which are constant-competitive for revenue and efficiency are derived.
Auctions with Dynamic Populations: Efficiency and Revenue Maximization
This work extends its results to revenue maximization, showing that a sequence of ascending auctions with asynchronous price clocks is an optimal mechanism for efficient allocation.
A multiple-choice secretary algorithm with applications to online auctions
A variation in which the algorithm is allowed to choose k elements, and the goal is to maximize their sum, which is the first algorithm whose competitive ratio approaches 1 as k ← ∞.
Limited and online supply and the bayesian foundations of prior-free mechanism design
The Bayesian optimal mechanism for these variants of auctions for selling a limited supply of a single commodity is described and the random sampling auction is extended to address the prior-free case.
Truthful auctions for pricing search keywords
We present a truthful auction for pricing advertising slots on a web-page assuming that advertisements for different merchants must be ranked in decreasing order of their (weighted) bids. This
Dynamic Revenue Maximization with Heterogeneous Objects: A Mechanism Design Approach
We study the revenue-maximizing allocation of several heterogeneous, commonly ranked objects to impatient agents with privately known characteristics who arrive sequentially. There is a deadline
Competitive analysis of incentive compatible on-line auctions
This paper studies auctions in a setting where the bidders arrive at di erent times and the auction mechanism is required to make decisions about each bid as it is received, and obtains several results, the cleanest of which is an incentive compatible on-line auction for a large number of identical items.