Code and Data Repository for A Proximal DC Algorithm for Sample Average Approximation of Chance Constrained Programming
The goal of this software is to demonstrate the effectiveness of the proximal DC method proposed in this paper for the chance constrained programming, as compared to other methods, as well as the effectiveness of the model when applied to empirical study.
Authors
- Qingyuan Kong (ORCID: https://orcid.org/0000-0002-8892-7235)
- Laura Balzano (ORCID: https://orcid.org/0000-0003-2914-123X)
- Rujun Jiang (ORCID: https://orcid.org/0000-0002-6610-6778)
- Peng Wang (ORCID: https://orcid.org/0000-0002-6799-0745)
Publication Details
- Journal
- INFORMS journal on computing
- Published
- 2025-03-14
- DOI
- https://doi.org/10.1287/ijoc.2024.0648.cd
- Primary Topic
- Optimization and Mathematical Programming
- Type
- article
- Field-Weighted Citation Impact
- 0.00