Skip to content
Haitao Li headshot

Haitao Li

Haitao Li

Professor and Chair of the Supply Chain & Analytics Department, College of Business Administration at University of Missouri – St Louis

Haitao Li is Professor and Chair of the Supply Chain & Analytics Department, College of Business Administration at University of Missouri – St Louis (UMSL). He holds his Ph.D. degree in operations management (2005), Master of Arts in economics (2002) from University of Mississippi, and Bachelor of Engineering in Foreign Trade in Industry with a minor in aeronautical engineering from Beijing University of Aeronautics and Astronautics, P.R. China (2000). Dr. Li has years of research experience in optimization modeling and algorithm design and has been actively working with industry and research institutes in the application domains of supply chain optimization, project scheduling, vehicle routing, and resource allocation, among others. He worked as a statistical analyst at the Naval Personnel Research, Study and Technology (NPRST) in Millington, TN in 2004, a visiting scholar at the Hewlett-Packard Laboratory (HPL) in Palo Alto, CA in 2005, and research consultant for HP Enterprises from 2010-2016. He has published in reputable scholarly journals including European Journal of Operational Research, Omega, Decision Sciences, Journal of the Operational Research Society, Computers and OR, Interfaces, Military Operations Research, Journal of Scheduling, Annals of Operations Research, among others. He was a recipient of the Young Investigator Award from the US Army Research Office (ARO) in 2010, the Douglas Durand Award for Research Excellence of UMSL in 2015. With two U.S. Patent applications and a number of invention disclosures, he was named 2015 UMSL Inventor of The Year. Dr. Li currently serves as Associate Editor of the Journal of the Operational Research Society and Transportation Journal, and Editorial Board member of the International Journal of Project Management.


Track: Supply Chain Analytics

Ameren Applies Advanced Analytics to Optimize Its Supply Networks

In this collaborative project with the Ameren Corp., the research team has developed a novel data-driven decision-support tool to simultaneously optimize the stocking location selection and inventory decisions under both demand- and supply-side uncertainties. Descriptive analytics is employed to characterize the probability distribution of uncertain parameters: demands and supply lead times of multiple product categories. These uncertain parameters, together with the risk of facility disruption estimated via predictive analytics, serve as inputs to a new mixed-integer nonlinear programming (MINLP) model to prescribe optimal solutions for strategic network design with joint stocking location and inventory decisions. The main innovation of the MNNLP model is its integrated framework built upon mathematical programming, inventory control and stochastic optimization, that explicitly accounts for the impacts of both demand uncertainty and supply risks, measured by lead time variation and disruption probability. Solutions generated from the decision-support tool enable Ameren to streamline and improve its supply networks with a potential savings of $1.8M. Additional sensitivity analyses form the basis for Ameren’s supply chain resiliency planning.