7 citations · 8 across the 2 of their papers we have counts for
3 papers
math.OC2023
A GNN-Guided Predict-and-Search Framework for Mixed-Integer Linear Programming
Qingyu Han, Linxin Yang, Qian Chen +5
Mixed-integer linear programming (MILP) is widely employed for modeling combinatorial optimization problems. In practice, similar MILP instances with only coefficient variations ar…
cs.LG2022★ 7 cited
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights
Maxime Gasse, Quentin Cappart, Jonas Charfreitag +38
Combinatorial optimization is a well-established area in operations research and computer science. Until recently, its methods have focused on solving problem instances in isolatio…
math.OC2022★ 1 cited
Efficient primal heuristics for mixed-integer linear programs
Akang Wang, Linxin Yang, Sha Lai +7
This paper is a short report about our work for the primal task in the Machine Learning for Combinatorial Optimization NeurIPS 2021 Competition. For each dataset of our interest in…