Timefold solver

The Open Source solver for scheduling and routing.
Build your own PlanningAI model in Java, Python or Kotlin.

✅ Apache License 2.0
✅ Available in Maven Central and PyPI
✅ Latest release: v1.13.0 - Aug 13, 2024

Use cases

Vehicle Routing Problem (VRP)

Quicker routes for a fleet of vehicles.

Maintenance scheduling

Timely upkeep of machinery and equipment.

Job Shop Scheduling

Reduce makespan for assembly lines.

Conference Scheduling

A better conference experience for attendees, speakers and organizers.

School timetabling

Compact schedules for teachers and students.

Employee scheduling

Assign shifts to employees by skills and availability.

Task Assignment

Assign tasks by priority, skills and affinity.

… and many more

Check out our quickstarts repository on GitHub.

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GitHub discussions

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Reliable

  • In production around the globe
  • Thousands of downloads per month
  • Fully documented
  • Thoroughly tested
  • Actively maintained

Timefold Solver is the continuation of Red Hat’s OptaPlanner by its creator and the team around it.

Compatible with

Timefold Solver is compatible with all major frameworks and platforms in the Java, Python and Kotlin ecosystems.
compatibility

Funding and sustainability

Timefold Solver is open source, released under the Apache License. It is free, including for commercial use. It solves any planning problem. The source code is on GitHub.

Timefold Solver is actively developed by Timefold, an Open Core company that builds ready-made enterprise models on top of it, to tackle complex scheduling and routing problems for their customers. Timefold also offers an Enterprise subscription with support and high-scalability features.

Start coding today

Solve your planning problem with Timefold Solver in Java, Python or Kotlin.

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Timefold

Timefold is an AI planning optimization platform, built on powerful open-source solver technology, enabling software builders to tackle real-world, complex and high-impact operational planning problems. It delivers significant economic value in optimization operations like extended VRP, maintenance scheduling, field service routing, task sequencing, etc.