Scheduling Optimization and Machine Learning¶
This is the start page for Scheduling Optimization and Machine Learning development. It tells you, as a developer of the integration from IFS Cloud to IFS Planning & Scheduling Optimization (PSO), what you need to know about the integration model and their implementations. It also describe the tools and skills needed. The main development tool in use is IFS Developer Studio.
Here is the full process for developing scheduling models:
- Use IFS Developer Studio to create or amend the integration model.
- Map entities as per the functional requirements by writing SQL.
- From the model generate and deploy the PL/SQL package.
- Refresh the Dictionary Cache.
- Create and configure a dataset based on the integration model in Scheduling Optimization Datasets page.
- Test the integration.
You might also begin your development process on any of the above steps, depending on your intents.
An overview of the development/testing flow is shown below:
- To develop new or edit existing Scheduling Optimization and Machine Learning models, you'll need to install the development tools for Base Server Development, that include the IFS Developer Studio tool.
- Developer Studio Integration
- Scheduling Model
- Machine Learning Model
- Scheduling Data
- Modeling Data
- System Data
- Change Detection
- Custom Change Detection
- Custom URL
- Handle Result
- Scheduling Optimization Interfaces
- Machine Learning Interfaces
Read more about Scheduling Optimization and Machine Learning.