A Simulation-based Performance Analysis of a Zone Picking System with Two Conveyor Lanes
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
A Simulation Study of the Vehicle Repositioning Policy with the Minimum and Maximum Service Levels in a Demand Responsive Transit System
New paper has been published in the Journal of the Korean Society of Supply Chain Management
Mixed-Integer Linear Programming and Constraint Programming Models for the Dual-lane Zone Picking System Operation
New paper has been published in the Journal of the Korean Society of Supply Chain Management
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