Multidimensional Dynamic Pricing for Welfare Maximization

Abstract

We study the problem of a seller dynamically pricing d distinct types of indivisible goods, when faced with the online arrival of unit-demand buyers drawn independently from an unknown distribution. The goods are not in limited supply, but can only be produced at a limited rate and are costly to produce. The seller observes only the bundle of goods purchased at each day, but nothing else about the buyer’s valuation function. Our main result is a dynamic pricing algorithm for optimizing welfare (including the seller’s cost of production) that runs in time and a number of rounds that are polynomial in d and the approximation parameter. We are able to do this despite the fact that (i) the price-response function is not continuous, and even its fractional relaxation is a non-concave function of the prices, and (ii) the welfare is not observable to the seller.

Document Details

Document Type
Pub Defense Publication
Publication Date
Feb 29, 2020
Source ID
10.1145/3381527

Entities

People

  • Aaron Roth
  • Aleksandrs Slivkins
  • Jonathan Ullman
  • Zhiwei Steven Wu

Organizations

  • Defense Advanced Research Projects Agency
  • Microsoft
  • National Science Foundation
  • Northeastern University
  • University of Minnesota
  • University of Pennsylvania

Tags

Fields of Study

  • Economics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • International Relations and European Studies
  • Life Cycle Cost Analysis