Ali Tolooie

Assistant Professor of Supply Chain Management

EducationAli Tolooie

  • Ph.D. degree in Industrial Engineering from Kansas State University, Manhattan, KS, USA. 2018-2022
  • M.S. in Industrial Engineering from University Technology Malaysia, Johor, Malaysia. 2013-2015
  • B.S. in Industrial Engineering from Iran. 2006-2010

Dr. Tolooie earned his Ph.D. in industrial engineering from Kansas State University and a master’s degree in industrial engineering at the University Technology Malaysia in Johor, Malaysia. He earned his B.S. in industrial engineering from Iran.

Before starting his Ph.D. program, he served as a research assistant at University Malaya, doing research on various supply chain and logistics project.

His research focuses on the modeling and optimization of stochastic supply chain systems. He has aimed to improve the reliability and resiliency of the supply chain network through the development of stochastic optimization models and methods to help address important problems related to product delivery on last-mile logistics.

To date, his work has resulted in more than seven top-tier peer-reviewed journals and seven conference presentations.

Courses Taught

  • Operation Research
  • Operation Management
  • Business Statistics

Specialization(s)

Optimization and Decision Making

Professional Interests

  • Supply Chain and Logistics Management
  • Applications of Operations Research in Supply Chain
  • Stochastic Modeling and Optimization
  • Data Analytics and Machine Learning

Recent Publications

  • Tolooie, A., Wu, H., Palani, A., Sinha, A., & Liu, X. (2022). A Multi-Cut L-Shaped Decomposition Algorithm for Stochastic Security Constrained Unit Commitment with Renewable Generation. Available at SSRN 4189386.
  • Maity, M., Tolooie, A., Sinha, A. K., & Tiwari, M. K. (2021). Stochastic batch dispersion model to optimize traceability and enhance transparency using Blockchain. Computers & Industrial Engineering, 154, 107134.
  • Tolooie, A., Maity, M., & Sinha, A. K. (2020). A two-stage stochastic mixed-integer program for reliable supply chain network design under uncertain disruptions and demand. Computers & Industrial Engineering, 148, 106722.
  • Google Scholar: https://scholar.google.com/citations?hl=en&user=ENerQVYAAAAJ

Contact Dr. Tolooie

478.301.2159
tolooie_a@mercer.edu

1501 Mercer University Drive
Macon, GA 31207
Stetson-Hatcher School of Business, Room 221