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Robust multidimensional pricing: separation without regret.

Authors :
Koçyiğit, Çağıl
Rujeerapaiboon, Napat
Kuhn, Daniel
Source :
Mathematical Programming. Nov2022, Vol. 196 Issue 1/2, p841-874. 34p.
Publication Year :
2022

Abstract

We study a robust monopoly pricing problem with a minimax regret objective, where a seller endeavors to sell multiple goods to a single buyer, only knowing that the buyer's values for the goods range over a rectangular uncertainty set. We interpret this pricing problem as a zero-sum game between the seller, who chooses a selling mechanism, and a fictitious adversary or 'nature', who chooses the buyer's values from within the uncertainty set. Using duality techniques rooted in robust optimization, we prove that this game admits a Nash equilibrium in mixed strategies that can be computed in closed form. The Nash strategy of the seller is a randomized posted price mechanism under which the goods are sold separately, while the Nash strategy of nature is a distribution on the uncertainty set under which the buyer's values are comonotonic. We further show that the restriction of the pricing problem to deterministic mechanisms is solved by a deteministic posted price mechanism under which the goods are sold separately. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00255610
Volume :
196
Issue :
1/2
Database :
Academic Search Index
Journal :
Mathematical Programming
Publication Type :
Academic Journal
Accession number :
160073109
Full Text :
https://doi.org/10.1007/s10107-021-01615-4