Docs
  • Solver
  • Models
    • Field Service Routing
    • Employee Shift Scheduling
    • Pick-up and Delivery Routing
  • Platform
Try models
  • Employee Shift Scheduling
  • Introduction
  • 1.21.x
    • latest
    • 1.21.x

Employee Shift Scheduling

    • Introduction
    • Getting started: Hello world
    • User guide
      • Terms
      • 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
      • Metrics and optimization goals
      • Score analysis
      • Visualizations
    • Employee resource constraints
      • Employee contracts
      • Employee availability
      • Employee priority
      • Pairing employees
      • Shift travel and locations
      • 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
      • Demand-based scheduling
      • Mandatory and optional shifts
      • Shift assignments
      • Skills and risk factors
    • 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

Introduction

The Employee Shift Scheduling model is one of Timefold’s Planning AI models and is available on the Timefold Platform.

The Employee Shift Scheduling model assigns shifts to employees with the goals of creating schedules that minimize labor costs, ensure proper shift coverage, and treats employees fairly and with respect.

The model runs on the Timefold Platform and the application includes Timefold Enterprise Solver, a scalable optimization engine that can solve complex constraint satisfaction problems.

The Employee Shift Scheduling model includes constraints for:

  1. Matching employee availability, skills, and preferences with shifts.

  2. Complying with labor law and regulations.

  3. Scheduling priority shifts.

  4. Managing shift rotations and patterns.

  5. Keeping shift assignments within budget.

To learn more about individual constraints, see the Employee resource constraints and Shift service constraints guides.

Employee shifts view
Figure 1. Visualization of an optimized employee shift schedule

Constraints have configurable weights, making them adjustable to meet different business goals and priorities.

The real-time planning API makes plans adaptable when unforeseen events inevitably occur, and the recommendations API can help you figure out which employees to assign to which shifts.

The REST API layer is defined on top of the model and serves as a communication point with the engine to provide a stable interface that allows you to manage the lifecycle of the optimization problem, from submitting the initial dataset to retrieving the final solution.

Introduction for integration & application developers

Backend developers, integration engineers, full-stack developers, and technical consultants implement the model in an application or workflow.

Concern Documentation

How to get a first working solution quickly

Getting started: Hello world

Correct API usage

Understanding the API, Integration, Dataset lifecycle

Understanding available constraints and features

Employee resource constraints and Shift service constraints

Debugging invalid inputs or unexpected results

Input validation

How the model supports reacting to unexpected events and replanning with the least amount of disruption

Real-time planning

Performance tuning

Configuration parameters and profiles

Introduction for platform & enterprise architects

Enterprise architects, solution architects, security architects, IT governance leads, and platform owners are responsible for system integration, compliance, and long-term maintainability.

Concern Documentation

How the model integrates into existing enterprise systems

Integration

API contracts, and long-term stability

Model maturity and versioning

Authentication, authorization, and request integrity

API keys, Member management and roles, Secrets management

Auditability of configuration changes

Reviewing the audit log

Risk profile, product security, data security and general trust

Trust

Introduction for product, business & decision makers

Product managers, project managers, business analysts, operations managers, and executives evaluate value, scope, and speed of delivery.

Concern Documentation

What business problems the model solves

Use case guide, Metrics and optimization goals

How results can be evaluated and explained to stakeholders

Interpreting dataset results, Validating an optimized plan with Explainable AI

How the model handles labor law compliance

Configuring labor law compliance

How the model handles employee well-being

Configuring employee well-being

How the model can support strategic decision making

Uncovering inefficiencies in operational planning, Balancing different optimization goals

Following up on new features

Changelog and Upgrade to the latest version

Whether the model can evolve with changing business needs

Feature requests

Next

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

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

The maximum number of shifts in a dataset is limited to 400,000 to ensure optimal performance and stability of the model. For larger datasets, please contact Timefold support.
  • © 2026 Timefold BV
  • Timefold.ai
  • Documentation
  • Changelog
  • Send feedback
  • Privacy
  • Legal
    • Light mode
    • Dark mode
    • System default