Faculty Publication: Dr. Wang

April 2021

My research interests lie in algorithm design, computer simulation modeling, optimal decision making, and their applications in operations and logistics. I have particular interests in computational algorithm development as the methodological tools from my work can potentially be used for a broad class of decision making and analysis problems in business and engineering fields.

Real-life decision making problems are both important and challenging oftentimes due to complex uncertainties. For instance, as studied in [1] border and port control processes are crucial for a nation’s security and economic prosperity. But such processes are usually overwhelming the limited border enforcement and subject to different sources of uncertainties such as unpredictable illegal entries of humans and contraband. The research in [1] addresses such complexity with robust computational models and solution methods. Clustering algorithms developed in [2] provides a generic solution framework for
many business analysis problems, e.g. market basket analysis, insurance fraud detection, social network security, etc. Being in the info/data era, data-driven methods play an increasingly important role in business and management decision making.

The basic premise is that border regions that have overwhelming levels of illegal immigration create an environment that is both chaotic and cluttered, overwhelming the capabilities of border enforcement entities such as the U.S. Border Patrol.

References:
1. Simulation optimization in security screening systems subject to budget and waiting time constraints. (with Tsai, S.C., Chen, H., and Zhang, G.), Naval Research Logistics. Online: https://onlinelibrary.wiley.com/doi/abs/10.1002/nav.21976?af=R

2. A dual reformulation and solution framework for regularized convex clustering problems, (with Pi,
J.X., and Pardalos, P.M.), European Journal of Operational Research, vol. 290, 844—856, 2021.