葛冬冬,上海交通大学智能计算研究院院长、安泰经济与管理学院特聘教授,中国运筹学会理事;中国运筹学会数学规划分会青年理事会副主任。杉数科技联合创始人、首席科学家。
教育背景
2024-至今,上海交通大学智能计算研究院院长、安泰经济与管理学院特聘教授。
2013-2023,上海财经大学, 信息管理与工程学院教授。
2009-2013,上海交通大学安泰经管学院,博导,讲师,副教授。
2009年,斯坦福大学,管理科学与工程系,运筹学博士。
1999年,南开大学,数学学士
教授课程
高等运筹与优化理论,博士必修。
优化理论与物流管理,硕士选修。
量化管理科学,新生研讨课。
线性与非线性优化,试点班必修课。
计算复杂度理论与算法设计,试点班必修课。
研究兴趣
1, 超大规模数学优化问题的理论、算法与软件研发,及其在供应链、制造、交通、能源、量子计算等领域的应用。
2, LP,MILP,SDP,SOCP等问题的算法理论分析与软件开发;
3, 基于GPU的新一代数学规划算法设计;
4, 国产GPU的类CUDA数值计算库函数建设;
5, 大模型训练推理中的算法优化,及决策大模型的训练与应用。
担任了国内首个开源数学规划软件LEAVES mathematical programming solver开发,领导了国内首个专业数学优化软件Cardinal Optimizer(COPT)开发,首个专业数学规划和数学优化求解器COPT的开发负责人。
在管理与运筹,优化理论,计算机理论科学,机器学习等多个顶级期刊和会议上,如Operations Research,?Mathematics of Operation Research, Mathematical Programming, FOCS, SODA, EC, ICML 等发表过论文。担任过多个国际著名期刊的特约审稿。
曾参与波音公司、谷歌街景地图、上海通用等等国内外公司的多个优化项目,担任杉数科技首席科学家,深度参与了多个业界合作的重要项目,如与京东,顺丰,永辉等多个公司供应链与新零售项目的合作。
科研项目
主持过
国家自然科学基金面上项目和青年项目,浦江人才计划,上财创新群体基金负责人等基金。
数学优化软件开发
1.Cardinal Optimizer(COPT): 领导了国内首个专业数学优化软件开发,目前有线性规划、整数规划、半定规划、二阶锥规划、二阶凸规划、混合整数二阶锥规划、混合整数半正定规划等模块,均在第三方测试榜单上排名世界前二,具体信息请参见:http://plato.asu.edu/bench.html, https://shanshu.ai/solver, 以及 Cardinal Optimizer (COPT) User Guide 2022, https://arxiv.org/abs/2208.14314
2.LEAVES mathematical programming solver: 国内首个开源数学规划软件,2016年发布,包括了线性规划、几何规划等模块。
代表论文
1. Reward Learning From Preference With Ties, J Liu, D Ge, R Zhu, Submitted to AAAI 2025. arXiv preprint arXiv:2410.05328,2024
2. Dispatching Automated Guided Vehicles Using Efficient Data-Driven Optimization. H Qin, X Zhao, J Liu, D Ge, R Zhu. Submitted to MSOM. Available at SSRN 4959037, 2024
3. Early Birds versus Last-Minute Arrivals: Empirical Evidence and Theoretical Analysis of Arrival Time Queueing Game,X Zhao, Y Ding, D Ge, X Xie,Submitted to MSOM. Available at SSRN 4955803,2024
4. Solving Integrated Process Planning and Scheduling Problem via Graph Neural Network Based Deep Reinforcement Learning,H Li, H Zhang, Z He, Y Jia, B Jiang, X Huang, D Ge,Submitted to AAAI 2025. arXiv preprint arXiv:2409.00968,2024
5. Accelerating Low-Rank Factorization-Based Semidefinite Programming Algorithms on GPU,Q Han, Z Lin, H Liu, C Chen, Q Deng, D Ge, Y Ye,arXiv preprint arXiv:2407.15049,2024
6. An enhanced alternating direction method of multipliers-based interior point method for linear and conic optimization,Q Deng, Q Feng, W Gao, D Ge, B Jiang, Y Jiang, J Liu, T Liu, C Xue, Y Ye, C zhang,INFORMS Journal on Computing,2024
7. ORLM: Training Large Language Models for Optimization Modeling,Z Tang, C Huang, X Zheng, S Hu, Z Wang, D Ge, B Wang,Submitted to OR. arXiv preprint arXiv:2405.17743,2024
8. Restarted Primal-Dual Hybrid Conjugate Gradient Method for Large-Scale Quadratic Programming,Y Huang, W Zhang, H Li, W Xue, D Ge, H Liu, Y Ye,Submitted to IJOC. arXiv preprint arXiv:2405.16160,2024
9. Sketched Newton Value Iteration for Large-Scale Markov Decision Processes,J Liu, C Xie, Q Deng, D Ge, Y Ye,Proceedings of the AAAI Conference on Artificial Intelligence 38 (12), AAAI 2024, 2024
10. Trust Region Methods For Nonconvex Stochastic Optimization Beyond Lipschitz Smoothness,C Xie, C Li, C Zhang, Q Deng, D Ge, Y Ye,The 38th Annual AAAI Conference on Artificial Intelligence AAAI 2024,2024
11. Learning to Pivot as a Smart Expert,T Liu, S Pu, D Ge, Y Ye,The 38th Annual AAAI Conference on Artificial Intelligence AAAI 2024,2024
12. A Low-Rank ADMM Splitting Approach for Semidefinite Programming,Q Han, C Li, Z Lin, C Chen, Q Deng, D Ge, H Liu, Y Ye,Major Revision on IJOC. arXiv preprint arXiv:2403.09133,2024
13. Decoupling Learning and Decision-Making: Breaking the Barrier in Online Resource Allocation with First-Order Methods,W Gao, C Sun, C Xue, D Ge, Y Ye,arXiv preprint arXiv:2402.07108,2024
14. Nonlinear modeling and interior point algorithm for the material flow optimization in petroleum refinery,F Dong, D Ge, L Yang, Z Wei, S Guo, H Xu,Electronic Research Archive 32 (2), 915-927,2024
15. A Homogenization Approach for Gradient-Dominated Stochastic Optimization,J Tan, C Xue, C Zhang, Q Deng, D Ge, Y Ye,The Conference on Uncertainty in Artificial Intelligence UAI 2024,2024
16. cuPDLP-C: A Strengthened Implementation of cuPDLP for Linear Programming by C language,H Lu, J Yang, H Hu, Q Huangfu, J Liu, T Liu, Y Ye, C Zhang, D Ge,arXiv preprint arXiv:2312.14832,2023
17. A Universal Trust-Region Method for Convex and Nonconvex Optimization,Y Jiang, C He, C Zhang, D Ge, B Jiang, Y Ye,arXiv preprint arXiv:2311.11489,2023
18. Solving Linear Programs with Fast Online Learning Algorithms,W Gao, D Ge, C Sun, Y Ye. ICML'23: Proceedings of the 40th International Conference on Machine Learning,2023
19. A Homogeneous Second-Order Descent Method for Nonconvex Optimization. Chuwen Zhang, Dongdong Ge, Chang He, Bo Jiang, Yuntian Jiang, Chenyu Xue, Yinyu Ye, Major Revision on Mathematics of Operations Research. 2023
20. Homogeneous Second-Order Descent Framework: A Fast Alternative to Newton-Type Methods,C He, Y Jiang, C Zhang, D Ge, B Jiang, Y Ye. Major Revision on Mathematical Programming. arXiv preprint arXiv:2306.17516,2023
21. Pre-trained Mixed Integer Optimization through Multi-variable Cardinality Branching,Y Chen, W Gao, D Ge, Y Ye,arXiv preprint arXiv:2305.12352,2023
22. Stochastic Dimension-reduced Second-order Methods for Policy Optimization,J Liu, C Xie, Q Deng, D Ge, Y Ye,arXiv preprint arXiv:2301.12174,2023
23. SOLNP+: A Derivative-Free Solver for Constrained Nonlinear Optimization,D Ge, T Liu, J Liu, J Tan, Y Ye,ACM Transactions on Mathematical Software, Accepted, 2024. arXiv preprint arXiv:2210.07160.
24. Cardinal Optimizer (COPT) user guide,D Ge, Q Huangfu, Z Wang, J Wu, Y Ye,arXiv preprint arXiv:2208.14314,2022
25. Bayesian dynamic learning and pricing with strategic customers,X Chen, J Gao, D Ge, Z Wang,Production and Operations Management 31 (8), 3125-3142,2022
26. DRSOM: A Dimension Reduced Second-Order Method,C Zhang, D Ge, C He, B Jiang, Y Jiang, Y Ye,arXiv preprint arXiv:2208.00208,2022
27. Randomized Branching Strategy in Solving SCUC Model,R Cao, Y Chen, W Gao, J Gao, Y Zhang, C Lu, D Ge,2022 4th International Conference on Power and Energy Technology,ICPET 2022
28. Hdsdp: Software for semidefinite programming,W Gao, D Ge, Y Ye,Minor Revision on ACM Transactions on Mathematical Software. arXiv preprint arXiv:2207.13862,2022
29. Optimization and operations research in mitigation of a pandemic,CH Chen, YH Du, DD Ge, L Lei, YY Ye,Journal of the Operations Research Society of China 10 (2), 289-304,2022
30. JD. com: Operations research algorithms drive intelligent warehouse robots to work,H Qin, J Xiao, D Ge, L Xin, J Gao, S He, H Hu, JG Carlsson,INFORMS Journal on Applied Analytics 52 (1), 42-55,2022
31. Uncertainty quantification for demand prediction in contextual dynamic pricing,Y Wang, X Chen, X Chang, D Ge,Production and Operations Management 30 (6), 1703-1717,2021
32. From an interior point to a corner point: smart crossover,D Ge, C Wang, Z Xiong, Y Ye,Minor Revision on IJOC. arXiv preprint arXiv:2102.09420,2021
33. A Gradient Descent Method for Estimating the Markov Chain Choice Model,L Fu, DD Ge,Journal of the Operations Research Society of China, 1-11,2021
荣誉奖励
2023年上海城市数字化转型“智慧工匠”。
2020年度中国运筹学会运筹应用奖。
2016年中国运筹学会青年科技奖。
2014年IBM中国区访问学者Excellent Project Award。