Haitao Li, Ph.D.

Dr. Li's primary goal as an educator is two-fold. First, to disseminate knowledge in my domains of expertise in Supply Chain and Analytics, and second, to cultivate students’ interest and ability to acquire and apply knowledge.

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Education

PhD, Production and Operations Management, The University of Mississippi, 2005

M.A. Economics, The University of Mississippi, 2002

B.E. International Trade and Aeronautical Engineering, Beijing University of Aeronautics and Astronautics, 2000

Courses

SCMA 3301 Intro to Supply Chain Management
SCMA 5320 Operations Management
SCMA 6331 Supply Chain Modeling
SCMA 7302 Advanced Optimization Methods

Research

Dr. Li's research projects have been funded by the National Science Foundation, U.S. Army Research Office, U.S. Department of Transportation, Association Supply Chain Management (ASCM), International Agricultural Trade and Research Consortium (IATRC), Missouri Agriculture and Small Business Development Authority (MASBDA), and HP Labs, Ameren, Express Scripts Inc., and Cass Information Systems in the private sector.

Dr. Li is the Director of Laboratory of Advanced Supply Chain Analytics (LASCA).

Awards Research Grants

PI, “Food Distribution System Design and Public Health”, sponsored by the University of Missouri South Africa Exchange Program, 2025-2026.

PI, “Collaborative Research with Cass Information Systems-Phase II”, sponsored by the Cass Information Systems, 2025 – 2027.

Co-PI, “Design of Transportation Network with Drones for Perishable Medical Product Delivery”, sponsored by Mid-America Transplant, St. Louis, 2025 to 2026.

PI, “Collaborative Research Projects with AMICSTL”, sponsored by Advanced Manufacturing Innovation Center St. Louis (AMICSTL), 2024.

Co-PI, “Rapid Detection Technologies and Decision-Support Systems for Safe, Equitable Food Systems: Phase II”, sponsored by the NSF Convergence Accelerator Program, 2023 2026.

PI, “University Transportation Center (UTC) Region 7 Consortium”, sponsored by the Department of Transportation, $4.5 million, 2023 – 2028.

Patents & Inventions

Li, H., K. Trout and A. Morey, “Data-Driven Decision-Support System for Sensor-Enabled Food Supply Chains”, U.S. Patent Application, Attorney Docket Number: 25UMS003/3510178.0043, March 2025.

M. Almasri, K. Trout, H. Li, A. Morey, A. Gu, V. Anand, and S. Zhang, “Pathogenic Sensing, Differentiation and Quantification Platforms,” Patent Application no. PCT/US2447452, 2024, pending.

V. Anand and H. Li, Blockchain Transactions Based on Participant Ranking, International Application under PCT, WO2024/050361A1, July 2024.

Li, H., Kate Trout and A. Morey (2023). Data-Driven Decision-Support System for Sensor-Enabled Food Supply Chains, Provisional Patent Application, Attorney Docket Number: P14416US00.

Li, H., C. Halmen and L. Yang (2022). Physical Resource Optimization System and Associated Method of Use, U.S. National Patent 11,334,824.

Selected Publications

de Alba, H., H. Li, A. Tellez-Crespo, C. A. Santos, J. E. Gomez-Rocha, M. C. Vargas, V. A. Regueira, L. Ramshaw, A. Ramirez-Nafarrate, Using Optimization and AI for Large-Scale Stochastic Resource Planning, Annals of Operations Research, forthcoming.

Peng, W., M. Xu, H. Li*, and X. Li (2026), Optimizing the Configuration of A Green Supply Chain, International Journal of System Sciences: Operations & Logistics, https://www.tandfonline.com/doi/full/10.1080/23302674.2026.2657018.

Li, H.*, R. Hennig, G. Kochenberger, F. Glover (2026), Quantum Bridge Analytics: A QUBO Approach to the Uncapacitated Facility Location Problem, Annals of Operations Research, https://link.springer.com/article/10.1007/s10479-026-07201-1.

Nie, D. and H. Li* (2026), Optimizing Agri-food Supply Chain Configuration for Mitigating both Supply- and Demand-Side Risks, Agriculture and Food Security, https://rdcu.be/e8S9c.

Li, H. (2026), Data-Driven Optimization for Modern Urban Logistics and Transportation: Modeling Framework and Applications, Urban Lifeline, Open Access: https://link.springer.com/10.1007/s44285-025-00060-5. Best Paper Award in the 2025 Urban Lifeline Symposium, Saitama, Japan.

Li, H.*, J. Parcell, and A. Roach (2025), Optimizing CEA Supply Chain: A Case Study of St. Louis USA, Agriculture, Vol. 15, No. 20, Open Access: 10.3390/agriculture15202129.

Yang, L., D. Dobrzykowski, H. Li, and W. Ellegood (2025), Reducing Hospital Procurement Costs through Vendor Contract Optimization: A Decision-Support Framework for GPOs, Production and Operations Management, https://doi.org/10.1177/10591478251390103.

Womer, K., B. Khalifeh, H. Li and J. Camm (2025), Estimating the Effects of Ramp-up and Learning using Performance Data, Journal of Defense Analytics and Logistics, https://doi.org/10.1108/JDAL-02-2025-0003.

Xie, F., Y. Li and H. Li* (2025), Integrating Simulation, Optimization, and Reinforcement Learning for a General Class of Stochastic Scheduling Problems, Expert Systems with Applications, Vol. 279, p.127488.

Peng, W., Z. Wang, F. Xie and H. Li* (2025), A Heuristic Approach for the Critical Chain Project Scheduling Problem Based on Resource Flows, Optimization and Engineering, Vol. 180, p.107054.

Flores, I. O., A. Anani, H. Li and A. Jalilzadeh (2025), Optimizing Transition: Investigating the Influence of Operational Parameters on Production Scheduling Optimization for Mines Transitioning from Open Pit to Block Caving Methods, Optimization and Engineering, Vol. 26, p.1041-1068.

Anani, A., I. O. Flores, H. Li and A. Jalilzadeh (2024), Heuristic and Exact Approaches to Optimize the Production Scheduling of Mines Transitioning from Open Pit to Block Caving, Mining, Metallurgy & Exploration, Vol. 41, p.3769-3787.

Li, H.*, W. Tang, and L. Mai (2024), A Game-Decision-Theoretic Approach to Optimize the Dynamic Credit Terms in Supply Chain Finance, Annals of Operations Research, Vol. 340, p.913-941.

Enayati, S., H. Li, J. Campbell and D. Pan (2023), Multi-Modal Vaccine Distribution Network Design with Drones, Transportation Science, Vol. 57, No. 4, p.1069-1095. (This paper won the 2024 Best Paper Award of Transportation Science.)

Subbiah, C., A. Hupman, H. Li, and J. Simonis (2022), Improving Software Development Effort Estimation with a Novel Design Pattern Model, INFORMS Journal of Applied Analytics (IJAA), Vol. 53, No. 3, 192-206.

Alidaee, B., H. Li, H. Wang and K. Womer (2021), Integer Programming Formulations in Sequencing with Total Earliness and Tardiness Penalties, Arbitrary Due Dates, and No Idle Time: A Concise Review and Extension, Omega, Vol. 103, 102446.

Xie, F., H. Li* and Z. Xu (2021), An Approximate Dynamic Programming Approach to Project Scheduling with Uncertain Resource Availabilities, Applied Mathematical Modeling, Vol. 97, p.226-243.

Li, F., Z. Xu and H. Li* (2021), A Multi-Agent Based Cooperative Approach to Decentralized Multi-Project Scheduling and Resource Allocation, Computer and Industrial Engineering, Vol. 151, 106961.

Li, H.*, D. Jiang and D. Li (2021), Optimizing the Configuration of a Food Supply Chain, International Journal of Production Research, Vol. 59, No. 12, p.3722-3746.

Yang, L., H. Li and J. Campbell (2020), Improving Order Fulfillment Performance through Integrated Inventory Management in a Multi-Item Finished Goods System, Journal of Business Logistics, Vol. 41, No. 1, p.54-66.

Solomon, S., H. Li, K. Womer, C. Santos (2019), Multi-Period Stochastic Resource Planning in Professional Service Organizations, Decision Sciences, Vol. 50, No. 6, p1281-1318.

Womer, K., H. Li, J. Camm, C. Osterman, R. Radhakrishnan (2017), Learning and Bayesian Updating in Long Cycle Made-to-order (MTO) Production, Omega, Vol. 69, p29-42.

Li, H.* and B. Alidaee (2016), Tabu Search for Solving the Black-and-White
Traveling Salesman Problem, Journal of the Operational Research Society, Vol. 67, No. 8, p1061-1079.

Li, H.* and K. Womer (2015), Solving Stochastic Resource-Constrained Project Scheduling Problems by Closed-loop Approximate Dynamic Programming, European Journal of Operational Research, Vol. 246, No. 1, p20-33.

Santos, C., T. Gonzalez, H. Li*, K.-Y. Chen, D. Beyer, S. Biligi, Q. Feng, R. Kumar, S. Jain, R. Ramanujan, A. Zhang (2013), HP Enterprise Services Uses Optimization for Resource Planning, Interfaces, Vol. 43, No. 2, p152-169.

Li, H.* and K. Womer (2012), Optimizing the Supply Chain Configuration for Make-to-Order Manufacturing, European Journal of Operational Research, Vol. 221, No. 1, p118-128.

Li, H.* and M. Amini (2012), A Hybrid Optimization Approach to Configure a Supply Chain for New Product Diffusion: A Case Study of Multiple-Sourcing Strategy, International Journal of Production Research, Vol. 50, No. 11, p3152–3171.

Li, H.* and K. Womer (2009), Scheduling Projects with Multi-Skilled Personnel by a Hybrid MILP/CP Benders Decomposition Algorithm, Journal of Scheduling, Vol. 12, No. 3, p281-298.

Consulting Experience

Hewlett-Packard Laboratory (HP Lab)
Naval Personnel Research, Study and Technology (NPRST)