Analysis of the Impact of Resource Allocation Strategy on the Scheduling of Core Defense Technology Project Agreements
New paper has been published in Korean Society of Industrial Management Systems
Welcome to the Simulation & Production Logistics laboratory!
Our simulation models investigate the production logistics.
Our machine learning applications optimize them.
Mission statement
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
Recent posts
Presentation at the 2024 INFORMS Annual Meeting (2024.10.21)
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 the Recent Digital Twin and Production Logistics Research at the University of Washington (2024.10.20)
The 3rd Joint Workshop on Recent Digital Twin and Production Logistics Research (DTPL) was held on August 20, 2024, at the University of Washington.
Ph.D. candidate Bosung Kim Received Silver Award at the 2024 Samsung Display Paper Competition
Ph.D. candidate Bosung Kim from Professor Soondo Hong’s research team won the Silver Award at the 2024 Samsung Display Paper Competition for their work on op...