Graph Neural Networks – Optimization Online

Machine Learning Algorithms for Assisting Solvers for Constraint Satisfaction Problems

Published: 2025/11/09

Applications - OR and Management Sciences, Combinatorial Optimization, Optimization in Data Science Boolean Satisfiability, Conflict-Driven Clause Learning, Constraint Satisfaction Problem, Graph Neural Networks, Hybrid Solvers, Lazy Clause Generation, Learned Heuristics, machine learning, Neuro-Symbolic Optimization, reinforcement learning, Transformer Models

This survey proposes a unifying conceptual framework and taxonomy that systematically integrates Machine Learning (ML) and Reinforcement Learning (RL) with classical paradigms for Constraint Satisfaction and Boolean Satisfiability solving. Unlike prior reviews that focus on individual applications, we organize the literature around solver architecture, linking each major phase—constraint propagation, heuristic decision-making, conflict analysis, and meta-level … Read more

COIL: A Deep Architecture for Column Generation

Published: 2022/09/06

Behrouz Babaki

Sanjay Dominik Jena

Linear Programming column generation, Graph Neural Networks, Imitation Learning, stabilization

Column generation is a popular method to solve large-scale linear programs with an exponential number of variables. Several important applications, such as the vehicle routing problem, rely on this technique in order to be solved. However, in practice, column generation methods suffer from slow convergence (i.e. they require too many iterations). Stabilization techniques, which carefully … Read more