Master student Sangcheon Eom Received the Outstanding Paper Presentation Award
Master student Sangcheon Eom from Professor Soondo Hong’s research team received the Outstanding Paper Presentation Award
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
Master student Sangcheon Eom from Professor Soondo Hong’s research team received the Outstanding Paper Presentation Award
New paper has been published in Korean Society of Industrial Management Systems
Bonggwon Kang gave an invited talk at the 2024 INFORMS Annual Meeting in Seattle, titled ‘Modular Calibration of a Digital Twin Model for Planning-Level Deci...
The 3rd Joint Workshop on Recent Digital Twin and Production Logistics Research (DTPL) was held on August 20, 2024, at the University of Washington.