Our simulation models investigate the production logistics.
Our machine learning applications optimize them.
The objective of the Simulation & Production Logistics (SimPL) Laboratory is to develop large-scale simulation models, operational algorithms, machine learning models that will improve the operations and productivity of logistics and related production systems. Active research areas include simulation optimization, material handling and self-organizing operations, and OR applications in warehousing, semiconductor, display, and automobile industries.
Business areas: Material handling and production logistics in distribution centers, container terminals, semiconductor and display fabs, and construction equipment assembly line
OR approaches: Large-scale simulations, machine learning models, and optimization models
Operational strategy: Simulation optimization, self-organizing/-balancing operations
The 2nd Joint Workshop on Recent Digital Twin and Production Logistics Research (DTPL) was held from August 11 to 16, 2024, at the University of Washington. ...
Master’s and doctoral students presented their thesis defenses in the first semester of 2024.
New paper has been published in Transportation Research Part E: Logistics and Transportation Review.
Bonggwon Kang gave presentations at the KSIE Spring Conference 2024
