Opti Repo optimizes cost and time factors related to relocation of empty containers by applying AI technology and
optimization algorithms. In order to predict accurate supply and demand and accusation plan we design a structure
that divides the service area of the Liner and continuously supplements the Opti Repo optimization algorithm through
repeated machine learning of the execution results.
[ DB set up ]
- Database for Optimized Reposition Plan
- Unique algorithms for data cleansing
- Data I/F with Vessel Stowage Plan
- Data analysis of basic data set, Route, Loading Plan, etc
[Optimization and AI / DL]
- Auto create Forbid O/D
- Recalculate the volume constraints of BSA in terms of voyage no.
- Plan refinement through deep learning of execution results
[Optimization and AI / DL]
- Apply accuracy improvement algorithm through prediction accuracy evaluation
- To improve the accuracy of the Daily Model, CBF Creator integration with AI technology
- Configure multiple models to self-simulation
