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Neil Geismar

Center for Executive Development Professorship in Business Administration
Department of Information and Operations Management

Education

Ph.D. Operations Management, University of Texas at Dallas
M.S. Operations Research, University of Texas at Dallas
M.S. Mathematics, University of Tennessee
B.S. Mathematics, Tulane University

Research Interest

Supply Chain Scheduling, Currency Supply Chains, Closed-Loop Supply Chains

Courses Taught

SCMT 336: Decision Support Systems
SCMT 688: Doctoral Seminar in Supply Chain Management

Biography

H. Neil Geismar is a Center for Executive Development Professor in the Mays Business School at Texas A&M University. He has a Ph.D. degree from the University of Texas at Dallas in Operations Management. His research addresses production scheduling, especially in the field of robotic cell scheduling; supply chain management, focusing on the coordination of the manufacturing and delivery functions through scheduling; and currency supply chains in different countries. He has served as a consultant to industrial clients to improve their productivity and profitability. His papers have appeared in a number of journals, including INFORMS Journal on Computing, Manufacturing and Services Operations Management, Production and Operations Management, SIAM Review, and IISE Transactions. He is a member of INFORMS and of POMS, in addition to serving as a Senior Editor for Production and Operations Management.

Research Publications

Abbey, J. D., Geismar, H. N., & Souza, G. C. (2018a). Improving remanufacturing core recovery and profitability through seeding. Production and Operations Management, 28(3), 610–627. https://doi.org/10.1111/poms.12937

Abbey, J. D., Geismar, H. N., & Souza, G. C. (2018b). Improving remanufacturing core recovery and profitability through seeding. Production and Operations Management, 28(3), 610–627. https://doi.org/10.1111/poms.12937

Akturk, M. S., Abbey, J. D., & Geismar, H. N. (2017). Strategic design of multiple lifecycle products for remanufacturing operations. IISE Transactions, 49(10), 967–979. https://doi.org/10.1080/24725854.2017.1336684