Type of Publication: Article in Journal

Risk-Averse Dynamic Pricing using Mean-Semivariance Optimization

Author(s):

Schlosser, R.; Gönsch, J.

Title of Journal:

European Journal of Operational Research

Volume (Publication Date):

310 (2023)

Number of Issue:

3

pages:

1151-1163

Keywords:

Revenue managementRisk managementMarkov decision processMean-semivariance optimizationDynamic pricing

Digital Object Identifier (DOI):

doi:10.1016/j.ejor.2023.04.002

Link to complete version:

https://doi.org/10.1016/j.ejor.2023.04.002

Citation:

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Abstract

In many revenue management applications risk-averse decision-making is crucial. In dynamic settings, however, it is challenging to find the right balance between maximizing expected rewards and avoiding poor performances. In this paper, we consider time-consistent mean-semivariance (MSV) optimization for dynamic pricing problems within a discrete MDP framework, which are shown to be NP hard. We present a novel fixpoint-based dynamic programming approach to compute risk-sensitive feedback policies with Pareto-optimal combinations of mean and semivariance. We illustrate the effectiveness and the applicability of our concepts compared to state-of-the-art heuristics. For various numerical examples the results show that our approach clearly outperforms all other heuristics and obtains a performance guarantee with less then 0.2% optimality gap. Our approach is general and can be applied to MDPs beyond dynamic pricing.