Paper Info
Title
Optimal Pricing To Minimize Maximum Regret With Limited Demand Information
Abstract
In this paper, we consider a pricing problem faced by a seller that sells a given inventory of some product over a short selling horizon with limited demand information. The seller knows only that the demand is a linear function of the price, but does not know the parameters involved in the demand function. However, the seller knows that each parameter involved in the demand function belongs to a known interval. The seller's objective is to determine the optimal price for the entire selling season to minimize the maximum regret, where the maximum regret is defined as the maximum possible loss of revenue due to not knowing the precise values of the parameters. We derive closed-form optimal solutions for the problem under all possible cases of input parameters and identify some structural properties of the solution. We conduct computational tests to compare our modeling approach with several benchmark approaches and report related insights. (c) 2020 Elsevier Ltd. All rights reserved.
Year
DOI
Venue
2020
10.1016/j.cor.2020.105070
COMPUTERS & OPERATIONS RESEARCH
Keywords
DocType
Volume
Revenue management, Pricing, Limited demand information, Regret, Parametric problems, Robust optimization
Journal
124
ISSN
Citations 
PageRank 
0305-0548
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Ming Chen100.34
Zhi-Long Chen241426.32