📝 Publications

Large Language Model-driven Large Neighborhood Search for Large-Scale MILP Problems
CCF-A CAAI-A TH-CPL-A
Huigen Ye, Hua Xu, An Yan, Yaoyang Cheng

• This paper introduces a dual-layer self-evolutionary LLM agent to automate neighborhood selection, discovering effective strategies with scant small-scale training data that generalize well to large-scale MILPs. [PDF] [Video] [BibTex]

Light-EvoOPT: A Lightweight Evolutionary Optimization Framework for Ultra-Large-Scale Mixed Integer Linear Programs
JCR Q1 CAAI-A Impact Factor=12.0
Huigen Ye, Hua Xu, Carlos A. Coello Coello

• This paper proposes Light-EvoOPT, a Lightweight Evolutionary Optimization Framework for Ultra-Large-Scale Mixed Integer Linear Programs. [PDF] [BibTex]

Light-MILPopt: Solving Large-scale Mixed Integer Linear Programs with Small-scale Optimizer and Small Training Dataset
CAAI-A TH-CPL-A
Huigen Ye, Hua Xu, Hongyan Wang

• This paper proposes Light-MILPopt, a lightweight large-scale optimization framework that only uses a small-scale optimizer and small training dataset to solve large-scale MILPs. [PDF] [Video] [BibTex]

GNN&GBDT-Guided Fast Optimizing Framework for Large-scale Integer Programming
CCF-A CAAI-A TH-CPL-A
Huigen Ye, Hua Xu, Hongyan Wang, Chengming Wang, Yu Jiang

• This paper presents a GNN&GBDT-guided fast optimizing framework for large-scale IPs that only uses a small-scale optimizer to solve large-scale IPs efficiently. [PDF] [Video] [BibTex]

Adaptive Constraint Partition Based Optimization Framework for Large-Scale Integer Linear Programming (Student Abstract)
CCF-A CAAI-A TH-CPL-A
Huigen Ye, Hongyan Wang, Hua Xu, Chengming Wang, Yu Jiang

• This paper presents a general adaptive constraint partition-based optimization framework (ACP) for large-scale IPs that can efficiently use any existing optimization solver as a subroutine. [PDF] [BibTex]

MILPBench: A Large-scale Benchmark Test Suite for Mixed Integer Linear Programming Problems
CAAI-B TH-CPL-B
Huigen Ye, Yaoyang Cheng, Hua Xu, Zhiguang Cao, Hanzhang Qin

• This paper introduce MILPBench, a large-scale benchmark suite comprising 100,000 MILP instances organized into 60 wellcategorized classes, which also includes a comprehensive baseline library featuring 15 mainstream solving methods. [PDF] [BibTex]