While job shop problems are more common in manufacturing settings, the range of the problem can encompases anything from project management to suplly chain logistics. Due to the complexity of these type of problems, they are best handle by a professional scheduler, project manager, or a planner. However, this create a scenario with a lot of pressure since these professionals has to think of various scenario to fit a 24 hour schedule and that only cover tthe best scenario without any reworks. In this study, I'm leveraging the kobe scheduling mentioned by the researchers from AbSolute to develop a data science/machine learning approach to these job scheduling problem.
- Data Engineering
- EDA
- Determine the loss function
- Model Hypothesis
To contribute, create your own branch, develop, test and make a pull request to develop branch.
Ken Trinh
MIT License