With high probability, Branch-and-Price explores at most n^O(log s) nodes for typical two-stage stochastic binary IPs, supported by an average-case integrality gap bound of O((log s log^2 n)/n).
Springer Science & Business Media, 2006
3 Pith papers cite this work. Polarity classification is still indexing.
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RLSCG uses reinforcement learning to adaptively select stabilization parameters in column generation, substantially reducing iterations and runtime on cutting stock problems compared to fixed rules and other learning baselines.
PACE interleaves active generation of diverse learners with subsequent pruning to produce smaller ensembles that retain performance and offer faithfulness guarantees.
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Probabilistic analysis of dual decomposition on two-stage stochastic integer programs
With high probability, Branch-and-Price explores at most n^O(log s) nodes for typical two-stage stochastic binary IPs, supported by an average-case integrality gap bound of O((log s log^2 n)/n).
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Learning to Control Stabilization in Column Generation
RLSCG uses reinforcement learning to adaptively select stabilization parameters in column generation, substantially reducing iterations and runtime on cutting stock problems compared to fixed rules and other learning baselines.
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PACE: Prune-And-Compress Ensemble Models
PACE interleaves active generation of diverse learners with subsequent pruning to produce smaller ensembles that retain performance and offer faithfulness guarantees.