Kamlesh Mathur, PhD, understands supply chain logistics, or the movement of goods from raw materials to finished products, and the crucial role it plays in business operations. His research focuses on the distribution aspects of the supply chain, providing management tools in two key areas. In the first, Mathur’s studies look at how efficient routing and scheduling of delivery vehicles used to distribute products can result in substantial savings for companies. His second topic considers the question of where to locate claim and service centers for the greatest efficiency and effectiveness.
Dr. Mathur’s research has appeared in numerous journals including Transportation Science, Computers and Operations Research, and European Journal of Operations Research. He is a member of the Institute for Operations Research and Management Science and sits on the editorial review board for the Journal of Business Logistics.
Dr. Mathur received his PhD from Case Western Reserve University. Since his appointment to the faculty at Weatherhead School of Management, he has taught such courses as Business Statistics and Quantitative Analysis, Computer Simulation, and Supply Chain Logistics.
- Business Statistics and Quantitative Analysis
- Foundations of Probability and Statistics
- Supply Chain Logistics
- Capstone Project in Business Analytics
- Computer Simulation
- Operations Analytics: Stochastic
- Predictive Modeling
Venkateshan, P., Mathur, K., Ballou, R. (2017). "A Two-echelon joint continuous-discrete location model." European Journal of Operational Research, 262(3) 1028-39.
Venkateshan, P., Mathur, K. (2015). "A Heuristic for the Multisource Weber Problem with Service Level Constraints." Transportation Science, 49(3), 472-83.
Venkateshan, P., Mathur, K. (2011). "An Efficient Column-Generation-Based Algorithm for Solving a Pickup-and-Delivery Problem." Computers & Operations Research, 38(12) 1647-55.
Venkateshan, P., Mathur, K., Ballou, R. (2010). "Locating and Staffing Service Centers Under Service Level." European Journal of Operations Research, 201(1) 55-70.