4 citations · 9 across the 4 of their papers we have counts for
4 papers
Branch Ranking for Efficient Mixed-Integer Programming via Offline Ranking-based Policy Learning
Zeren Huang, Wenhao Chen, Weinan Zhang +7
Deriving a good variable selection strategy in branch-and-bound is essential for the efficiency of modern mixed-integer programming (MIP) solvers. With MIP branching data collected…
Grassland: A Rapid Algebraic Modeling System for Million-variable Optimization
Xihan Li, Xiongwei Han, Zhishuo Zhou +3
An algebraic modeling system (AMS) is a type of mathematical software for optimization problems, which allows users to define symbolic mathematical models in a specific language, i…
Learning to Optimize Industry-Scale Dynamic Pickup and Delivery Problems
Xijun Li, Weilin Luo, Mingxuan Yuan +5
The Dynamic Pickup and Delivery Problem (DPDP) is aimed at dynamically scheduling vehicles among multiple sites in order to minimize the cost when delivery orders are not known a p…
Bilevel Learning Model Towards Industrial Scheduling
Longkang Li, Hui-Ling Zhen, Mingxuan Yuan +5
Automatic industrial scheduling, aiming at optimizing the sequence of jobs over limited resources, is widely needed in manufacturing industries. However, existing scheduling system…