Planning optimization made easy.

Timefold is the open source AI solver to optimize operations and scheduling in Java, Python or Kotlin. Timefold is a fork of OptaPlanner by its creator and other experts.

Timefold can help you solve

Field Service Routing
Reduce fuel costs and boost Field Team productivity with Timefold’s Planning AI. Automate complex scheduling to save planning time and optimize field operations efficiently.
Employee scheduling
Timefold’s employee scheduling API platform automates planning so you can schedule shifts for thousands of employees, keep all constraints in mind and minimize overtime.
Last Mile Delivery Routing
Timefold’s last mile delivery routing Planning AI optimizes the final leg of the delivery process resulting in efficient delivery fleet management and minimized wasteful planning.
Vehicle Routing (VRP)
Determines the most efficient routes for a fleet of vehicles to visit multiple destinations, considering factors like distance, vehicle capacity, time windows, and customer preferences to optimize delivery or service operations.
Maintenance Scheduling
Timefold’s maintenance scheduling Planning AI automates and optimizes your technicians’ schedules to reduce overall downtime and achieve higher operational efficiency.
Job Shop Scheduling
Allocates resources and schedules production tasks in manufacturing environments with diverse equipment and processes, aiming to minimize idle time, maximize throughput, and meet delivery deadlines.
Food packaging
Designs efficient packaging processes for food products, considering factors like product integrity, shelf life, regulatory compliance, and cost-effectiveness, while ensuring food safety and quality standards are met.

View all models

Recent updates

Load balancing and fairness in constraints
Discover how to bring fairness to your Timefold solution
Employee Shift Scheduling AI in Python
Create feasible, automated employee shift schedules. Need to optimize for cost, service quality, and employee morale all at the same time? Let Timefold’s planning AI empower you to do this in Python.
Field Service Routing - Dealing with Timezones and Daylight Saving Time
Discover how to tackle time zones and daylight saving time in field service routing with Timefold. Optimize your schedules and avoid operational hiccups.
Optimize routing and scheduling in Python: a new open source solver Timefold
Automate and optimize your operations scheduling in Python with Timefold AI
Upgrade from OptaPlanner to Timefold in less than 1 minute
In this tutorial, we’ll show you how to effortlessly upgrade your OptaPlanner code to Timefold code in less than 1 minute. Co-founded by Geoffrey De Smet, the creator of OptaPlanner, Timefold is revolutionary planning optimization software designed to supercharge your planning processes
Shift hours and overtime for the Vehicle Routing Problem
How do you make field service technicians work the right amount of time? When is overtime a good thing? And how do you plan all that as efficiently as possible?
How to speed up Timefold Solver Startup Time by 20x with native images
Discover how to build a Spring native image and the benefits from doing so.
Quarkus Insights #162: What is Timefold AI?
Geoffrey De Smet joins us to discuss Timefold - an open source solver AI - and how it can used with Quarkus to optimize vehicle routing, maintenance scheduling, production lines and other planning problems.
Red Hat: OptaPlanner End Of Life Notice (EOL)
Timefold, led by former core OptaPlanner engineers, offers a seamless transition with extended support and accelerated innovation.

Loved by developers, trusted by enterprises

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.

10k+
technician vehicles
-25%
driving time
-10M
kg CO² emissions

Exploring Timefold: Optimizing Your Planning Experience

Experience a new era of planning optimization with Timefold. Dive into the world of efficient planning, enhanced performance, and user-centric solutions that empower you to excel in every aspect of your business.

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.
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 and fixes through Maven Central and Pypi.
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: an 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.
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: Handle changing circumstances & minimize impact on existing solutions.
- Overconstrained planning: When there are not enough resources, suggest alternative solutions.
- Real-time planning: React on real-time disruptions of the plan within milliseconds.
Compatible
Timefold is compatible with your favorite technology stack & cloud providers.

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.

Quickstart repo