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Employee Shift Scheduling

    • Introduction
    • Getting started: Hello world
    • User guide
      • Terminology
      • Use case guide
      • Planning AI concepts
      • Integration
      • Constraints
      • Understanding the API
      • Demo datasets
      • Input datasets
        • Model configuration
        • Model input
        • Planning window
      • Planning window
      • Time zones and Daylight Saving Time (DST)
      • Tags and tag types
      • Input validation
      • Output datasets
        • Metadata
        • Model output
        • Input metrics
        • Key performance indicators (KPIs)
      • Metrics and optimization goals
      • Score analysis
      • Visualizations
    • Employee resource constraints
      • Employee contracts
      • Employee availability
      • Employee priority
      • Pairing employees
      • Shift travel and locations
      • Shift Breaks
      • Employee activation
      • Work limits
        • Minutes worked per period
        • Minutes worked in a rolling window
        • Minutes logged per period
        • Days worked per period
        • Days worked in a rolling window
        • Consecutive days worked
        • Shifts worked per period
        • Shifts worked in a rolling window
        • Weekend minutes worked per period
        • Weekends worked per period
        • Weekends worked in a rolling window
        • Consecutive weekends worked
      • Time off
        • Days off per period
        • Consecutive days off per period
        • Consecutive days off in a rolling window
        • Consecutive minutes off in a rolling window
        • Shifts to avoid close to day off requests
        • Consecutive weekends off per period
      • Shift rotations and patterns
        • Shift rotations
        • Single day shift sequence patterns
        • Minimize gaps between shifts
        • Multi-day shift sequence patterns
        • Daily shift pairings
        • Overlapping shifts
        • Shift start times differences
        • Minutes between shifts
      • Shift type diversity
        • Shift tag types
        • Shift types worked per period
        • Unique tags per period
      • Fairness
        • Balance time worked
        • Balance shift count
    • Shift service constraints
      • Alternative shifts
      • Cost management
        • Cost groups
        • Employee rates
      • Demand-based scheduling
      • Mandatory and optional shifts
      • Skills and risk factors
      • Shift assignments
        • Shift selection
        • Employee selection
    • Manual intervention
    • Recommendations
    • Real-time planning
    • Real-time planning (preview)
    • Scenarios
      • Configuring labor law compliance
      • Configuring employee well-being
    • Changelog
    • Upgrade to the latest version
    • Feature requests

Metadata

The metadata object includes information about the metadata for the dataset:

{
  "metadata": {
    "id": "ID",
    "parentId": "ID",
    "originId": "ID",
    "name": "dataset name",
    "submitDateTime": "2026-03-10T12:15:50-04:00",
    "startDateTime": "2026-03-10T12:15:50-04:00",
    "activeDateTime": "2026-03-10T12:15:50-04:00",
    "completeDateTime": "2026-03-10T12:15:50-04:00",
    "shutdownDateTime": "2026-03-10T12:15:50-04:00",
    "solverStatus": "DATASET_CREATED",
    "score": "0hard/0medium/100000soft",
    "tags": [
      "Control"
    ],
    "validationResult": {
      "summary": "OK",
      "errors": [
        "Error message"
      ],
      "warnings": [
        "Warning message"
      ]
    },
    "failureMessage": "string"
  }
}
  • id is the ID assigned to the dataset.

  • parentId identifies the dataset this dataset was derived from if the patch operation was used to create a new revision of the dataset.

  • originID identifies the original dataset this dataset was derived from if multiple patch operation were used to create new revisions of the dataset.

  • name is the name that was provided with the input dataset. If no name was provided, one will be automatically generated.

  • submitDateTime is when the dataset was submitted.

  • startDateTime is when the dataset started solving.

  • activeDateTime shows when the solve-phase of the run started.

  • completeDateTime shows when the solve-phase of the run stopped.

  • shutdownDateTime shows when the solver shut down.

  • solverStatus shows the status of the dataset. See dataset lifecycle for more details.

  • score is the hard, medium, and soft scores of the dataset. See constraints for more information about constraint scores.

  • tags contains any tags that were included with the input dataset.

  • validationResult will return VALIDATION_NOT_SUPPORTED, OK, WARNINGS, ERRORS.

  • errors contains the list of errors that occurred during validation.

  • warning contains a list of warnings for the dataset, if any occur.

  • failureMessage describing the reason the run failed if the solverStatus is SOLVING_FAILED.

Next

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

  • Learn more about employee shift scheduling from our YouTube playlist.

  • Learn about Model output object included in output datasets.

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