4 papers
iScheduler: Reinforcement Learning-Driven Continual Optimization for Large-Scale Resource Investment Problems
Yi-Xiang Hu, Yuke Wang, Feng Wu +3
Scheduling precedence-constrained tasks under shared renewable resources is critical to modern computing platforms. It is often modeled as the Resource Investment Problem (RIP) by…
Scalable Mixed-Integer Optimization with Neural Constraints via Dual Decomposition
Shuli Zeng, Sijia Zhang, Feng Wu +2
Embedding deep neural networks (NNs) into mixed-integer programs (MIPs) is attractive for decision making with learned constraints, yet state-of-the-art monolithic linearisations b…
CLCR: Contrastive Learning-based Constraint Reordering for Efficient MILP Solving
Shuli Zeng, Mengjie Zhou, Sijia Zhang +3
Constraint ordering plays a critical role in the efficiency of Mixed-Integer Linear Programming (MILP) solvers, particularly for large-scale problems where poorly ordered constrain…
Beyond Local Selection: Global Cut Selection for Enhanced Mixed-Integer Programming
Shuli Zeng, Sijia Zhang, Shaoang Li +2
In mixed-integer programming (MIP) solvers, cutting planes are essential for Branch-and-Cut (B&C) algorithms as they reduce the search space and accelerate the solving process. Tra…