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Bibliographic Details
Main Authors: Tian, Lai, Royset, Johannes O.
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2507.15801
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Table of Contents:
  • In this paper, we show how approximating Rockafellians serve as a principled and effective alternative for improving the stability of stochastic programs under distributional changes. Unlike previous efforts that focus on special distributions and continuous integrands, our results accommodate general probability distributions and discontinuous integrands. Thus, our results apply to chance-constrained programs, for which we obtain improved qualitative and quantitative stability results under weaker assumptions pertaining to metric subregularity and upper outer-Minkowski content.