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Shengbin Wang

Associate Professor of Management

Phone: (609) 771-2153


Office: Business Building 230

Office Hours: Monday & Thursday 3:30-4:50pm


Dr. Shengbin Wang is an Associate Professor of Management in the School of Business at The College of New Jersey. He received his PhD in Management with a major in Supply Chain Management from Rutgers University, and his BS in Applied Mathematics from Zhejiang University in China. Prior to joining The College of New Jersey, Dr. Wang taught at North Carolina A&T State University, Rutgers University, and University of Wisconsin. Dr. Wang’s primary research interests lie in supply chain operations modeling and algorithm design, humanitarian operations management, big data analytics in supply chain management, large scale lateral transshipment, and last mile delivery network design. He has many publications in peer reviewed journal, conference proceedings, and book chapters. Dr. Wang’s teaching interests include operations management, supply chain management, supply chain design and analysis, business statistics, and enterprise resource planning (SAP ERP). His teaching philosophy is to create a student-centered learning environment. He loves to engage students in and out of classrooms, and always shows his passion in teaching and learning processes. Dr. Wang is also a recipient of several research awards from NC A&T State University and Rutgers University.

Peer-Reviewed Publications

  1. “Discovering Communities for Microgrids with Spatial-Temporal Net Energy”, Xie, S., Wang, H., and Wang, S., et al., Journal of Modern Power Systems and Clean Energy, 2019,
  2. “Integrated Disaster Medical Assistance Team Scheduling and Relief Supply Distribution”, Wang, , Liu, F., Hong, Y., and Chen, H., International Journal of Logistics Management, 2018, 29 (4), pp.1279-1305.
  3. “A Hybrid Distance Matrix Based Algorithm for Solving Traveling Salesman Problem”, Wang, S., Rao, W., and Hong, Y., Operational Research: an International Journal, 2018.
  4. “Achieving Optimal Safety Inventory Levels for Oil Companies using the CONWIP Approach”, Leaven, L., Wang, S., Coley, L., and Udoka, S., International Journal of Supply Chain Management, 2017, 6 (4), pp. 17-21.
  5. “On the Robust and Stable Flowshop Scheduling under Stochastic and Dynamic Disruptions”, Liu, F., Wang, S., Hong, Y., and Yue, X., IEEE Transactions on Engineering Management, 2017, 64 (4), pp. 539-553.
  6. “Efficient Energy Consumption Scheduling: Towards Effective Load Leveling”, Hong, Y., Wang, S., and Huang, Z., Energies, 2017, 10 (1), Article 105.
  7. “An Efficient Two-Objective Hybrid Local Search Algorithm for Solving the Fuel Consumption Vehicle Routing Problem”, Rao, W., Liu, F., and Wang, S., Applied Computational Intelligence and Soft Computing, 2016, Article ID 3713918.
  8. “Personnel Scheduling and Supplies Provisioning in Emergency Relief Operations”, Lei, L., Pinedo, M., Qi, L., Wang, , and Yang, J., Annals of Operations Research, 2015, 235 (1), pp. 487-515.
  9. “A Survey of Privacy-aware Supply Chain Collaboration: From Theory to Applications”, Hong, Y., Vaidya, J., and Wang, , AAA Journal of Information Systems (JIS), 2014, 28 (1), pp. 243-268.
  10. “Operations Scheduling with Multiple Resources and Transportation Considerations”, Lee, K., Lei, L., Pinedo, M., and Wang, , International Journal of Production Research (IJPR), 2013, 51 (23-24), pp. 7071-7090.
  11. “Urgent Epidemic Control Mechanism for Aviation Networks”, Peng, C., Wang, , Shi, M., and Jin, X., Practical Applications of Intelligent Systems Advances in Intelligent and Soft Computing, 2012(124), pp. 355-360.
  12. “Discovering Energy Communities for Microgrids on the Power Grid”, Hong, Y., Goel, S., Lu, H., and Wang, , Proceedings of 2017 IEEE International Conference on Smart Grid Communications: Data Management and Grid Analytics, Dresden, Germany.
  13. “The Integrated Disaster Medical Assistance Team Scheduling and Relief Supply Distribution Problem”, Wang, , Proceedings of 2017 Washington Business Research Forum, Washington, D.C., USA.
  14. “Achieving Optimal Safety Inventory Levels for Oil Companies using the CONWIP Approach”, Leaven, L., Wang, S., Coley, L., and Udoka, S., Proceedings of 12th Annual London Business Research Conference, 2017, Imperial College, London, UK.
  15. “Integrated production/distribution/routing planning for supply chain networks: A review”, Chapter 1 in Supply Chain Management and Logistics: Innovative Strategies and Practical Solutions, CRC Press, Taylor & Francis Group, “Industrial and Systems Engineering” series, 2015.


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