An Intersection Cutting Plane Algorithm for Chance-Constrained Programs with Finite Support
Year: 2026
Type: preprint
Abstract: Standard Big-M mixed-integer programming reformulations of chance-constrained programs (CCPs) with finite support often yield weak linear relaxations and scale poorly as the number of scenarios increases. To address this limitation, we derive two families of intersection cuts from problem-specific S-free sets and develop decomposition-based branch-and-cut frameworks. The first one exploits the submodular structure of the scenario requirement function, while the second one uses probability covers. We propose hybrid separation strategies that combine classical mixing inequalities and quantile cuts with the proposed intersection cuts. Computational experiments on integrated production-distribution planning instances show that the proposed hybrid methods reduce computational time compared to pure methods.
Source: arXiv (Cornell University)
Authors: Pathy, Soumya Ranjan, Rahimian, Hamed
Institution: Clemson University
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
Awards: G2013088438, G2640189751, MRI: Acquisition of a Cyberinstrument for Interdisciplinary Computational Science and Engineering, G3595647918, G4753560203, MRI: Acquisition of a Cyberinstrument for AI-Enabled Computational Science & Engineering, G7090116110, MRI: Acquisition of High Performance Computing Instrument for Collaborative Data-Enabled Science, II NEW: Infrastructure to Support Research in Network-Aware Data-Intensive Computing, G8419962090
OpenAlex ID: W7214766639