Planning optimization
made easy

Timefold is the open source AI solver
to optimize operations and scheduling
in Java, Python or Kotlin code.

Timefold is a fork of OptaPlanner
by its creator and other experts.

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Timefold can
help you solve

Discover all 8 planning models
Vehicle Routing (VRP)
Vehicle Routing (VRP)

Quicker routes for a fleet of vehicles.

Maintenance Scheduling
Maintenance Scheduling

Timely upkeep of machinery and equipment.

Job Shop Scheduling
Job Shop Scheduling

Reduce the makespan for assembly and manufacturing lines.

Loved by developers,
trusted by enterprises

All references
Field Service Routing

Enterprises optimized their field service technicians routes

Every day their service technicians drive to locations across the country to perform field service jobs. Every job has skill requirements. Most visits have a limited time window. With this technology, enterprises reduced the driving time of their fleet by more than 25%. That significantly increased employee productivity, because technicians spend less time driving and more time working. It also lowered their fuel consumption noticeably.

kg CO²
Maintenance Scheduling

Companies optimized their field equipment maintenance scheduling

Machines - deployed at their customers - require regular maintenance. To prevent out of order incidents, their service engineers clean and repair them frequently. Definitely on time. But ideally also just in time, for productivity reasons. Some machines are used more often than others: those require more frequent visits. With this technology, companies increased their completed maintenance by 25% and improved equipment reliability for their customers.

Employee scheduling

Governments optimized their case scheduling

A government department of an entire country relies on this technology to assign week-long cases to government workers. Schedules adhere to skill requirements, location vicinity, PTO and day-off requests and more.

Employee scheduling

Hospitals optimized their employee scheduling

Every week, hospitals in US, EU and Australia automate and optimize assigning shifts to employees with this technology. Their schedules take into account day off requests, skill requirements, department affinity, overtime, labor laws, publication notice and more.


Real world

Many optimization solvers are designed for academic or isolated problems, such as the Traveling Salesman Problem, VRP, Bin Packing or Job Shop Scheduling.
In reality, planning problems are more complex. They combine hard/soft constraints from different use cases and often include country or company specific constraints.

Timefold was created to automate real world planning optimization with ease. Solve for hard, soft and other constraints. Reduce costs substantially, improve service quality, fulfill employee wishes and lower carbon emissions. Far more than expected.

Easy to use

Traditionally, optimization solvers are the domain of mathematicians and expensive, specialized Operations Research consultants. You feed those solvers your data as number matrices and your constraints as mathematical equations.

Timefold is build for programmers. You feed it your data as domain classes and define your constraints as code. Let us worry about the math inside the solver. Your code becomes self-explanatory. Integration with other APIs is straightforward. And when the business rules change constraints - they eventually always do - maintenance is easy.

This is a revolution in the world of planning optimization, and a central element in the mission of our company, to increase the accessibility of planning optimization.

Open source

Timefold Community is Open Source software, released under the Apache License 2.0. Use it in your commercial software, for free. It's a complete and professional solver. We frequently release new features, enhancements and fixes through Maven Central (Java, Kotlin) and Pypi (Python).

Our entire company believes in the power of open source to build high-quality software. Our team participates in the open source community and regularly contributes to other open source projects.

To pay for Timefold Community development, we sell Timefold Enterprise: a Source Available extension with high-scalability features and enterprise support.

Scalable and fast

Timefold is extremely fast. It combines performance tricks from metaheuristic algorithms, concurrent programming, database indexes and incremental (delta) calculations with native compilation support.

But speed without scaling is irrelevant. The search space of planning problems scales exponentially to the size of the problem. The quality of a solver on a small dataset says nothing about that solver on a big dataset.

Timefold is arguably the most scalable production solver on this planet. Like other solvers, it's CPU-bound with little to no I/O. Unlike other solvers, memory consumption barely increases as you scale out, making it ideal for cloud deployments.

Operational fit

Timefold is build for operational planning, not just strategic or tactical planning. We deeply understand that a schedule is living, breathing thing. That its requirements change over time. That planning agility is essential for great results. Therefore, Timefold handles:

  • Continuous planning: Publish a schedule every week, several weeks before execution.
  • Pinning: Your user is still in control. Timefold plans around their manual assignments.
  • Non-disruptive replanning: Deal with changing circumstances, but minimize changes to the published schedule.
  • Overconstrained planning: When there are too few resources to cover all the work, help find a solution.
  • Real-time planning: React on real-time disruptions of the plan within milliseconds.


Timefold integrates with your favorite cloud, language, framework and libraries.

Let's get you started

Optimize your planning with Timefold today

Take a look at our guides and conquer your first planning problem today. Explore our quickstart examples and copy/paste it to get started. Customize it, integrate it, deploy it, scale it and then watch how your organization becomes more efficient.

Start coding now


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