Adaptive solution prediction for combinatorial optimization
From MaRDI portal
Publication:6112875
DOI10.1016/j.ejor.2023.01.054arXiv2204.08700OpenAlexW4318562161MaRDI QIDQ6112875
No author found.
Publication date: 10 July 2023
Published in: European Journal of Operational Research (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2204.08700
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Greedy function approximation: A gradient boosting machine.
- An exact approach for the vertex coloring problem
- Stabilized column generation
- Learning heuristics for the TSP by policy gradient
- An efficient evolutionary algorithm for the orienteering problem
- Accelerating the branch-and-price algorithm using machine learning
- Learning when to use a decomposition
- Machine learning for combinatorial optimization: a methodological tour d'horizon
- MIPLIB 2017: data-driven compilation of the 6th mixed-integer programming library
- Predicting solutions of large-scale optimization problems via machine learning: a case study in blood supply chain management
- Guiding high-performance SAT solvers with unsat-core predictions
- Random sampling and machine learning to understand good decompositions
- On learning and branching: a survey
- Reinforcement learning for combinatorial optimization: a survey
- Deep-learning-based partial pricing in a branch-and-price algorithm for personalized crew rostering
- Branch-and-Price: Column Generation for Solving Huge Integer Programs
- Column Generation based Primal Heuristics
- A survey on vertex coloring problems
- Emergence of Scaling in Random Networks
- The Evolution of Random Graphs
- A Column Generation Approach for Graph Coloring
- Solving the Orienteering Problem through Branch-and-Cut
- Estimating the Size of Branch-and-Bound Trees
- Selected Topics in Column Generation
- Solution of a Large-Scale Traveling-Salesman Problem
- Constraint Integer Programming: A New Approach to Integrate CP and MIP