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Journal ArticleDOI

Robust Multi-Product Pricing

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TLDR
In this paper, the authors formulate the multi-ambiguity multi-product robust pricing problem as a worst-case stochastic intensity control problem where ambiguity is modeled using the notion of relative entropy.
Abstract
This paper concerns dynamic pricing of multiple perishable products when there is model uncertainty, which we formulate as a worst-case stochastic intensity control problem where ambiguity is modeled using the notion of relative entropy. One feature of our formulation is that the demand models for different products can have different levels of ambiguity, a situation that arises (for instance) if a new product is being sold along side an established one. We show that this multiple-ambiguity multi-product robust pricing problem is equivalent to another (non-standard) risk-sensitive pricing problem, and show that it can be decentralized under additional assumptions on the demand rate model. The risk-sensitive problem has several unusual features: (i) the net income from sales of each product is valued by its certainty equivalent under an exponential utility function where the aversion parameter is determined by the level of ambiguity of its demand model, (ii) the overall goal is to maximize the sum of the certainty equivalents over all products, and (iii) products making sales are required to compensate other products for the use of commonresources according to a revenue sharing rule. We characterize the revenue sharing rule which leads to an equivalence between the risk-sensitive problem we have just described and the original robust pricing problem. This generalizes risk-sensitive/robust control duality to the case where different components of the model have different levels of model uncertainty. Finally, we show that the robust multi-product problem can be decentralized and solved in terms of modified robust/risk-sensitive single-product problems, if the demand rate functions satisfy certain independence assumptions. The modification of the single product problems involves the introduction of a cost to account for the value of inventory that is used at each sale. This cost is closely related to the revenue sharing rule associated with the robust/risk-sensitive control equivalence.

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References
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Journal ArticleDOI

The Price of Robustness

TL;DR: In this paper, the authors propose an approach that attempts to make this trade-off more attractive by flexibly adjusting the level of conservatism of the robust solutions in terms of probabilistic bounds of constraint violations.

The price of the robustness

D Bertsimas, +1 more
TL;DR: An approach is proposed that flexibly adjust the level of conservatism of the robust solutions in terms of probabilistic bounds of constraint violations, and an attractive aspect of this method is that the new robust formulation is also a linear optimization problem, so it naturally extend to discrete optimization problems in a tractable way.
Journal ArticleDOI

MAxmin expected utility with non-unique prior

TL;DR: In this paper, the authors characterize preference relations over acts which have a numerical representation by the functional J(f) = min > {∫ uo f dP / P∈C } where f is an act, u is a von Neumann-Morgenstern utility over outcomes, and C is a closed and convex set of finitely additive probability measures on the states of nature.
Journal ArticleDOI

Robust Convex Optimization

TL;DR: If U is an ellipsoidal uncertainty set, then for some of the most important generic convex optimization problems (linear programming, quadratically constrained programming, semidefinite programming and others) the corresponding robust convex program is either exactly, or approximately, a tractable problem which lends itself to efficientalgorithms such as polynomial time interior point methods.
Book

The Theory and Practice of Revenue Management

TL;DR: In this article, the authors present the economics of RM, including single-resource capacity control, network capacity control and overbooking, as well as dynamic pricing and auctioning.
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