SHSP: Structure-Aware Hierarchical Solution Prediction for Mixed-Integer Linear Programming

arXiv:2608.25282 · cs.LG, cs.AI · Submitted 2026-08-26 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-08-26

Updated: 2026-08-26

Code: https://github.com/lamda-bbo/SHSP

Terminology

• Benchmark — 26× in this paper · explained in 2 episodes
• Graph Construction — 9× in this paper · explained in 3 episodes
• Mixed-Integer Linear Programming — 8× in this paper
• Ablation — 7× in this paper · explained in 1 episode
• Ablation study — 7× in this paper · explained in 1 episode
• Reinforcement Learning — 6× in this paper · explained in 4 episodes
• Combinatorial Optimization — 5× in this paper · explained in 2 episodes
• Decode — 5× in this paper · explained in 2 episodes
• Neural Diving — 4× in this paper
• Set Covering — 3× in this paper
• Combinatorial Auctions — 2× in this paper
• Embeddings — 2× in this paper · explained in 2 episodes
• GNNs — 2× in this paper · explained in 2 episodes
• Workload Appointment — 2× in this paper
• Accuracy — 1× in this paper · explained in 1 episode
• Adaptive Selection — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Alternation — 1× in this paper · explained in 1 episode
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Core — 1× in this paper · explained in 2 episodes
• Graph Neural Networks (GNNs) — 1× in this paper · explained in 7 episodes
• Hybrid Models — 1× in this paper · explained in 2 episodes
• Local Optimization — 1× in this paper · explained in 2 episodes
• Objective Function — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• StructureAware Hierarchical Solution Prediction — 1× in this paper

Sources

• Lookback for Learning to Branch
• LLM4Branch: Large Language Model for Discovering Efficient Branching Policies of Integer Programs
• Learning to Select Cuts for Efficient Mixed-Integer Programming
• Machine Learning Insides OptVerse AI Solver: Design Principles and Applications
• Solving Mixed Integer Programs Using Neural Networks
• Confidence Threshold Neural Diving
• Effective Generation of Feasible Solutions for Integer Programming via Guided Diffusion

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