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research article

Robust Multidimensional Pricing: Separation without Regret

Kocyigit Yalcin, Cagil  
•
Rujeerapaiboon, Napat  
•
Kuhn, Daniel  
2022
Mathematical Programming

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.

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Type
research article
DOI
10.1007/s10107-021-01615-4
Author(s)
Kocyigit Yalcin, Cagil  
•
Rujeerapaiboon, Napat  
•
Kuhn, Daniel  
Date Issued

2022

Published in
Mathematical Programming
Volume

196

Start page

841

End page

874

Subjects

Robust optimization

•

Pricing

•

Mechanism design

•

Regret minimization

Note

Available from Optimization Online

URL
http://www.optimization-online.org/DB_HTML/2018/07/6742.html
Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
RAO  
Available on Infoscience
July 26, 2018
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/147582
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