Dr. Norman's primary research interests include logistics and the application of operations research models to production and logistics systems.
His research considers both theoretical developments and issues concerning the practical application of operations research models.
His research focuses primarily on three aspects of logistics.
The first concerns the development of mathematical models for scheduling manufacturing resources and personnel in both manufacturing and service organizations.
Specific scheduling environments include: metal cutting machine tools, manufacturing shop floors, and personnel training.
Second, he is investigating methods for achieving efficient facility design and material handling in manufacturing and service environments.
Third, he is a member of the University of Pittsburgh's RFID Center for Excellence and conducts research related to the application of RFID technologies to enhance supply chain management and for asset management and control.
Dr. Norman also conducts research concerning manufacturing process analysis and energy modeling.
In his research, he employs traditional optimization approaches such as math and dynamic programming, and heuristic solution techniques including: evolutionary computation and tabu search.
Systems modeling, analysis, and optimization using computational
intelligence (evolutionary algorithms, tabu search, artificial neural
networks) combined with classical operations research methods. Application
areas of interest include: production and personnel scheduling, process
planning, facility layout and design, and manufacturing process
control.
