This Small Grant for Exploratory Research (SGER) formulates multi-scale spatial modeling procedures for handling data in various details to support solution of complex logistics optimization problems. The investigators develop reliability concepts useful in the logistics field for solving homeland security related problems. Finally, this project integrates probability and statistical models with operations research tools to improve seaport container-operation efficiency to meet the needs of security inspections.
Evaluation and design of secure and reliable supply-chain logistics networks are of critical importance to the modern U.S. economy. In particular, balancing security and efficiency objectives in the design and operation of transportation logistics systems and seaport container inspections is vitally important, and to do so presents unique mathematical and statistical modeling challenges. This interdisciplinary team of statisticians and logisticians will bring years of experience in research and education to explore the potential in this field. The key scientific impact of this project is that the theory and methods developed in this project serve as the foundation for advances in multi-scale data modeling and hierarchical decision-analysis tools. This project also provides several broader impacts required by the NSF, e.g., collaboration with industry for disseminating research results, education of high-quality students through thesis advising and class teaching (with case studies explored in this project), and support of summer research experience for students from underrepresentated groups.
