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.

v1.12.0Jul 9th, 2024
  • NEC
  • e-switch Solutions
  • Equina
  • OptaZEN
  • HawkEye 360
  • NEC
  • e-switch Solutions
  • Equina
  • OptaZEN
  • HawkEye 360
  • NEC
  • e-switch Solutions
  • Equina
  • OptaZEN
  • HawkEye 360

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.

Recent updates

  • 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.

  • Time Windows for Vehicle Routing

    In this short video Geoffrey De Smet explains how Time Windows work.

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.

    • Microsoft Azure
    • Google Cloud
    • Java
    • Python
    • Kotlin
    • Spring
    • Quarkus
    • Maven
    • Gradle
    • PyPi
    • Docker
    • Kubernetes
    • Amazon Web Services (AWS)
    • Microsoft Azure
    • Google Cloud
    • Java
    • Python
    • Kotlin
    • Spring
    • Quarkus
    • Maven
    • Gradle
    • PyPi
    • Docker
    • Kubernetes
    • Amazon Web Services (AWS)

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

Meet Timefold at

  • Devoxx Belgium 2024

    Flag of BE
    Antwerp, Belgium
    October 7th, 2024 - October 11th, 2024
  • KotlinConf 2024

    Flag of DK
    Copenhagen, Denmark
    May 23rd, 2024 - May 24th, 2024
  • Live stream: Vehicle Routing

    Flag of CZ
    Brno, Czech Republic
    April 17th, 2024
  • Fosdem

    Flag of BE
    Brussels, Belgium
    February 3rd, 2024
  • BeJUG

    Flag of BE
    Ghent, Belgium
    December 5th, 2023
  • Slush

    Flag of FI
    Helsinki, Finland
    November 29th, 2023 - December 1st, 2023
  • Devoxx Belgium 2023

    Flag of BE
    Antwerp, Belgium
    October 2nd, 2023
  • Java 21 Launch Event

    Online, Remote
    September 19th, 2023

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