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In the past, you’ve worked with OptaPlanner. This globally used Open Source software was at the core of a wide array of planning optimization projects, significantly impacting efficiency in diverse industries. My co-founder, Geoffrey De Smet, the creator of OptaPlanner, and I witnessed first-hand the transformative impact of this technology. Driven by our mission to Free the world from wasteful scheduling we decided to build upon this legacy. Thus, Timefold was born.

As announced on May 2nd, 2023, OptaPlanner continues as Timefold. When the future of OptaPlanner at Red Hat seemed uncertain, we took the initiative to ensure that this vital technology not only survives but also thrives. Timefold represents not merely a stable continuation but also an evolution - a new chapter. We already fixed a good number of bugs and released new features. Timefold is twice as fast, and comes with better documentation. But this is just the start as our ambition reaches far higher into making our planning optimization products as accessible and easy to use as database technology or even spreadsheets!

We are honored to welcome the core OptaPlanner team - Lukas, Radovan, and Christopher - to Timefold. Their expertise and insights are invaluable in our journey ahead. We are proud of the Timefold team and thankful for being on this ride together.

Timefold is more than a tool; it’s a community and a movement. Your contributions, feedback, and ideas are the keystones of this community. Find us on StackOverflow or star us on GitHub.

We invite you to continue on this journey with us. We will send out a monthly newsletter that we will keep informative and on-point. Feedback is always welcome. We look forward to your continued support and engagement!

Why upgrade OptaPlanner to Timefold?

For reliability, features and speed. Timefold adds features and fixes bugs, many that still reside in OptaPlanner. Timefold is twice as fast as OptaPlanner out-of-the-box. Here’s how to upgrade OptaPlanner to Timefold.

OptaPlanner versus Timefold bugfixes
OptaPlanner versus Timefold performance

Releases

Timefold Solver Community Edition 1.5.0 full release notes

Featured Update: Recommended Fit API, designed for appointment scheduling. Whilst on a call, operators can receive a list of appointment choices, ranked from best fit to worst, for informed decision-making. Also, score corruption errors now provide better debugging information.

Timefold Solver Community Edition 1.4.0 full release notes

Featured Update: JSON-friendly score explanations. Timefold Solver can now break down the score all the way to individual constraint matches. It can also compute differences between any two solutions. Also, Spring Boot integration has improved significantly.

Here you can find all previous releases of Timefold Solver.

Latest Timefold videos

What the team likes about Timefold Solver.

Coding the capacitated VRP in Java

Geoffrey De Smet & Lukáš Petrovický at Devoxx Belgium

Continue reading

  • Java versus Python performance benchmarks on PlanningAI models

    Discover the techniques Timefold Engineers deploy to make your Python code faster.

  • Simplify the Shadow Variable Listener Implementation

    Learn how to simplify creating listeners for planning list variables with the new shadow variable @CascadingUpdateShadowVariable.

  • Load balancing and fairness in constraints

    Discover how to bring fairness to your Timefold solution

  • Optimize routing and scheduling in Python: a new open source solver Timefold

    Automate and optimize your operations scheduling in Python with Timefold AI

  • Timefold Solver Python live in Alpha

    Empowering developers to solve planning problems

  • 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.

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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.

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