Learning generalized strong branching for set covering, set packing, and 0-1 knapsack problems

DOI10.1016/j.ejor.2021.11.050zbMath1506.90175OpenAlexW3216362854MaRDI QIDQ2140266

Natashia Boland, Yu Yang, Bistra Dilkina, Savelsbergh, Martin W. P.

Publication date: 20 May 2022

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2021.11.050

zbMATH Keywords

branch and boundmachine learningbinary optimization

Mathematics Subject Classification ID

Mixed integer programming (90C11) Polyhedral combinatorics, branch-and-bound, branch-and-cut (90C57) Learning and adaptive systems in artificial intelligence (68T05) Combinatorial optimization (90C27)

Related Items (2)

\textsc{Ner4Opt}: named entity recognition for optimization modelling from natural language ⋮ Last‐mile delivery with drone and lockers

Uses Software

• CPLEX
• XGBoost

Cites Work

• Unnamed Item
• Branching rules revisited
• Machine learning for combinatorial optimization: a methodological tour d'horizon
• Optimization problems for machine learning: a survey
• The voice of optimization
• On learning and branching: a survey
• Backdoor Branching
• Experiments in mixed-integer linear programming using pseudo-costs
• Branch and Bound Methods for Mathematical Programming Systems
• A Computational Study of Search Strategies for Mixed Integer Programming
• Multivariable Branching: A 0-1 Knapsack Problem Case Study
• Mixed Integer Programming: Analyzing 12 Years of Progress
• Experiments in mixed-integer linear programming
• A Machine Learning-Based Approximation of Strong Branching
• Gene selection for cancer classification using support vector machines

This page was built for publication: Learning generalized strong branching for set covering, set packing, and 0-1 knapsack problems