Learned Pairwise Deep Dual-Optimal Inequalities for Stabilizing Column Generation
Column generation (CG) is central to many large-scale optimization algorithms, including branch-price-and-cut methods for vehicle routing problems, but unstable dual solutions can substantially slow its convergence. Existing deep dual-optimal inequalities can reduce this instability by restricting the dual space. Their construction, however, typically relies on problem-specific exchange arguments that are difficult to establish for routing problems with capacity limits, time windows, and other resource constraints. We introduce learned pairwise deep dual-optimal inequalities (L-PDDOIs), a learning framework that predicts pairwise orderings between dual variables and incorporates their pri...
| Authors | Zhengzhong Ricky You, Bo Tang, Haoran Liu et al. |
|---|---|
| Primary category | math.OC |
| Published | 15 July 2026 |
| Last updated at source | 15 July 2026 |
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