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Risk-aware Fund Allocation based on Time-Series Forcasting
Official implementation of "COExpander: Adaptive Solution Expansion for Combinatorial Optimization".
ML4CO-Bench-101: Benchmark Machine Learning for Classic Combinatorial Problems on Graphs.
Awesome machine learning for combinatorial optimization papers.
The code for "Apollo-MILP: An Alternating Prediction-Correction Neural Solving Framework for Mixed-Integer Linear Programming", Haoyang Liu, Jie Wang, Zijie Geng, Xijun Li, Yuxuan Zong, Fangzhou Zh…
Python interface to automatically formulate Machine Learning models into Mixed-Integer Programs
Benchmarking GNN datasets for PowerGrids - node level regression tasks
Two stage heuristic method to reconfigure the distribution networks
Developed and implemented a Mixed-Integer Linear Programming (MILP) model for microgrid operation optimization, leveraging renewable energy sources and hydrogen storage. The model simulates two ope…
Tools for building power systems optimization problems
This GitHub github contains the codes and data used in the research work entitled "A Learning-to-Optimize Framework for Joint Scheduling in Electricity and Gas Systems" by Chloé Dupont, François Va…
[ICLR 2023] "On Representing Mixed-Integer Linear Programs by Graph Neural Networks" by Ziang Chen, Jialin Liu, Xinshang Wang, Jianfeng Lu, Wotao Yin.
MISO: Learning Multiple Initial Solutions to Optimization Problems
This is the *Clp* version of our code for *Accelerate Presolve in Large-Scale Linear Programming via Reinforcement Learning*.
Deep Reinforcement Learning for optimizing inventory management using MILP and reinforcement learning algorithms.
Code for our paper: ACM-MILP: Adaptive Constraint Modification via Grouping and Selection for Hardness-Preserving MILP Instance Generation
GNN&GBDT-Guided Fast Optimizing Framework for Large-scale Integer Programming(Ye et al., ICML 2023): https://openreview.net/pdf?id=tX7ajV69wt
[NeurIPS 2024 Datasets and Benchmarks Track] Benchmarking PtO and PnO Methods in the Predictive Combinatorial Optimization Regime
Source code accompanying the 'An end-to-end attention-based approach for learning on graphs' paper
code for paper "DRoC: Elevating Large Language Models for Complex Vehicle Routing via Decomposed Retrieval of Constraints"
The code of paper Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model. Zhihai Wang, Xijun Li, Jie Wang*, Yufei Kuang, Mingxuan Yuan, Jia Zeng, Yongdong Zhan…