Multidimensional Dynamic Pricing for Welfare Maximization

Author:

Roth Aaron1,Slivkins Aleksandrs2,Ullman Jonathan3,Wu Zhiwei Steven4

Affiliation:

1. University of Pennsylvania, Philadelphia, PA, USA

2. Microsoft Research, New York, NY, USA

3. Northeastern University, Boston, MA, USA

4. University of Minnesota, Minneapolis, MN, USA

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. We derive this result as an application of a general technique for optimizing welfare over divisible goods, which is of independent interest. When buyers have strongly concave, Hölder continuous valuation functions over d divisible goods, we give a general polynomial time dynamic pricing technique. We are able to apply this technique to the setting of unit-demand buyers despite the fact that in that setting the goods are not divisible, and the natural fractional relaxation of a unit-demand valuation is not strongly concave. To apply our general technique, we introduce a novel price randomization procedure that has the effect of implicitly inducing buyers to “regularize” their valuations with a strongly concave function. Finally, we also extend our results to a limited-supply setting in which the supply of each good cannot be replenished.

Funder

Sloan Foundation Fellowship

NSF

DARPA

Publisher

Association for Computing Machinery (ACM)

Subject

Computational Mathematics,Marketing,Economics and Econometrics,Statistics and Probability,Computer Science (miscellaneous)

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