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Task Scheduling

    • Introduction
    • Getting started: Hello world
    • User guide
      • Terminology
      • Scheduling API concepts
      • Integration
      • Constraints
      • Using the API
        • Using the OpenAPI spec
        • API tooling
      • Demo datasets
      • Input datasets
        • Model configuration
        • Model input
      • Output datasets
        • Metadata
        • Model output
        • Input metrics
        • Key performance indicators (KPIs)
      • Job types and machine types
      • Resource-specific durations
      • Freeze jobs until
      • Metrics and optimization goals
      • Score analysis
      • Validation
    • Machine and employee resource constraints
      • Machine unavailability
      • Resource transitions
      • Employee resources
    • Job service constraints
      • Time windows
      • Time management
      • Job dependencies
      • Priority jobs
      • Tags and specific resources
    • Real-time planning
    • Changelog
    • Upgrading to the latest versions
    • Feature requests

Demo datasets

Timefold Platform includes Task Scheduling demo datasets that you can use to explore the functionality of the model and the platform.

You can access the demo datasets in the platform UI or with the API.

1. Use the demo datasets in the UI

To access the demo dataset in the UI:

  1. Log into Timefold Platform: app.timefold.ai

  2. Select the Task Scheduling tile.

  3. Click + New plan.

  4. Select a demo dataset, and click Run.

2. Use the demo datasets with the API

To get the list of available demo datasets and information about each dataset from the API, make the following call:

curl -X GET -H 'X-API-KEY: <API_KEY>' https://app.timefold.ai/api/models/job-scheduling/v1/demo-data

To download the BASIC demo dataset, make the following API call:

curl -X GET -H 'X-API-KEY: <API_KEY>' https://app.timefold.ai/api/models/job-scheduling/v1/demo-data/BASIC -o sample.json

To post the demo dataset for solving, use the following API call:

The output from the POST operation includes a metadata ID that you need for subsequent commands.
curl -X POST -H 'X-API-KEY: <API_KEY>' https://app.timefold.ai/api/models/job-scheduling/v1/schedules [email protected]

To get the current status and score of the dataset, replace <ID> with the identifier from the previous post operation and make the following API call:

curl -X GET -H 'X-API-KEY: <API_KEY>' https://app.timefold.ai/api/models/job-scheduling/v1/schedules/<ID>/metadata

To get the complete schedule, replace <ID> with the identifier from the previous post operation and make the following API call:

curl -X GET -H 'X-API-KEY: <API_KEY>' https://app.timefold.ai/api/models/job-scheduling/v1/schedules/<ID>

Next

  • See the full API spec or try the online API.

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