Analysis and control of an SEIR epidemic system with nonlinear transmission rate. - Na Yi; Qingling Zhang 001; Kun Mao 001; Dongmei Yang; Qin Li (Math. Comput. Model., 2009)

Lagrangian heuristic for scheduling a steelmaking-continuous casting process. - Kun Mao 001; Quan-Ke Pan; Mehmet Fatih Tasgetiren (CISched, 2013)

An Effective Artificial Bee Colony Algorithm for a Real-World Hybrid Flowshop Problem in Steelmaking Process. - Quan-Ke Pan; Ling Wang 001; Kun Mao 001; Jin-Hui Zhao; Min Zhang (IEEE Trans Autom. Sci. Eng., 2013)

A novel Lagrangian relaxation approach for a hybrid flowshop scheduling problem in the steelmaking-continuous casting process. - Kun Mao 001; Quan-Ke Pan; Xinfu Pang; Tianyou Chai (Eur. J. Oper. Res., 2014)

Solving the steelmaking casting problem using an effective fruit fly optimisation algorithm. - Junqing Li 001; Quan-Ke Pan; Kun Mao 001; Ponnuthurai N. Suganthan (Knowl. Based Syst., 2014)

A discrete teaching-learning-based optimisation algorithm for realistic flowshop rescheduling problems. - Junqing Li 001; Quan-Ke Pan; Kun Mao 001 (Eng. Appl. Artif. Intell., 2015)

An Effective Subgradient Method for Scheduling a Steelmaking-Continuous Casting Process. - Kun Mao 001; Quan-Ke Pan; Tianyou Chai; Peter B. Luh (IEEE Trans Autom. Sci. Eng., 2015)

A Hybrid Fruit Fly Optimization Algorithm for the Realistic Hybrid Flowshop Rescheduling Problem in Steelmaking Systems. - Junqing Li 001; Quan-Ke Pan; Kun Mao 001 (IEEE Trans Autom. Sci. Eng., 2016)

The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. - Maxime Gasse; Simon Bowly; Quentin Cappart; Jonas Charfreitag; Laurent Charlin; Didier Chételat; Antonia Chmiela; Justin Dumouchelle; Ambros M. Gleixner; Aleksandr M. Kazachkov; Elias B. Khalil; Pawel Lichocki; et al. (NeurIPS (Competition and Demos), 2021)

An Improved Reinforcement Learning Algorithm for Learning to Branch. - Qingyu Qu; Xijun Li; Yunfan Zhou; Jia Zeng; Mingxuan Yuan; Jie Wang 005; Jinhu Lv; Kexin Liu; Kun Mao 001 (CoRR, 2022)

Learning to Reformulate for Linear Programming. - Xijun Li; Qingyu Qu; Fangzhou Zhu; Jia Zeng; Mingxuan Yuan; Kun Mao 001; Jie Wang 005 (CoRR, 2022)

The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. - Maxime Gasse; Quentin Cappart; Jonas Charfreitag; Laurent Charlin; Didier Chételat; Antonia Chmiela; Justin Dumouchelle; Ambros M. Gleixner; Aleksandr M. Kazachkov; Elias B. Khalil; Pawel Lichocki; Andrea Lodi 001; et al. (CoRR, 2022)

LaTeX2Solver: a Hierarchical Semantic Parsing of LaTeX Document into Code for an Assistive Optimization Modeling Application. - Rindra Ramamonjison; Timothy T. L. Yu; Linzi Xing; Mahdi Mostajabdaveh; Xiaorui Li; Xiaojin Fu; Xiongwei Han; Yuanzhe Chen; Ren Li; Kun Mao 001; Yong Zhang 004 (ACL (demo), 2023)

Machine Learning Insides OptVerse AI Solver: Design Principles and Applications. - Xijun Li; Fangzhou Zhu; Hui-Ling Zhen; Weilin Luo; Meng Lu; Yimin Huang; Zhenan Fan; Zirui Zhou; Yufei Kuang; Zhihai Wang; Zijie Geng; Yang Li 197; et al. (CoRR, 2024)

Fitness Landscape of Large Language Model-Assisted Automated Algorithm Search. - Fei Liu 044; Qingfu Zhang 001; Xialiang Tong; Kun Mao 001; Mingxuan Yuan (CoRR, 2025)

SMARTAPS: Tool-augmented LLMs for Operations Management. - Timothy Tin Long Yu; Mahdi Mostajabdaveh; Jabo Serge Byusa; Rindra Ramamonjison; Giuseppe Carenini; Kun Mao 001; Zirui Zhou; Yong Zhang 004 (CoRR, 2025)