Timefold Solver 2.0 released

The open source release comes with additional support for complex scheduling and routing cases, a new API to escape local optima and faster solving. This release also lays the groundwork for our upcoming explainability, insights and integration functionality.

However, we’re also making some open source changes, for long term sustainability. More on that below.

# New features

# List variables, all grown up

Timefold Solver 1.0 already had basic support for list variables. These are typically used for vehicle routing problems (VRP) and job shop scheduling (JSS). For example: a vehicle has a list of visits. In 2.0, list variables are now fully supported across all solver features, such as:

• Pinning visits
• Allow visits to remain unassigned (no more dummy vehicles)
• Limit the value ranges per entity (reduce the search space)

This enabled us to remove chained variables: list variables are faster, easier and cleaner in every aspect.

# Custom shadow variables

Some solving decisions are a result of other solving decisions. Arrival time in VRP for example. The order of the visits determines the arrival time for each visit. Such data naturally belongs in shadow variables.

Timefold Solver 1.0 had basic support for shadow variables. In 2.0, shadow variables are concise to define, straightforward to unit test, and protected from accidental loops out of the box.

# Neighborhoods API to escape local optima

Out-of-the-box, Timefold Solver’s algorithms escape most local optima. However, some advanced use cases benefit greatly from custom move selection. Until now, implementing custom move selection was error-prone, verbose and limited.

Our new Neighborhoods API fixes this. It’s a clean, declarative API to define high-quality custom move selection with only a few lines of code. Similar to Constraint Streams, you can enumerate the planning entities and values, define how to sample from them, and optionally filter out combinations to only generate useful moves. Change and swap moves are available out of the box. Try it out.

# Faster solving, same clean code

Since Timefold Solver 1.0, we've steadily added features that unlock meaningful performance gains. Here are a few worth knowing about.

• Precomputed joins cache the static parts of a Constraint Stream, the parts that only depend on problem facts. so the solver stops redoing the same work on every move.
• toConsecutiveSequences replaces chains of self-joins with a single collector, making one of the most common patterns in scheduling significantly cheaper.
• Shadow variable handling has been reworked to cut overhead on every variable change, which compounds across millions of moves.
• Constraint Profiling shows exactly which constraints are costing you time, so you know where to focus.

On a real-world course scheduling problem, three targeted rewrites using these features delivered a 91% speedup over a Solver version not using these features. You can learn more about this in a future blog post and during our upcoming Solver 2.0 webinar!

# Smaller wins worth knowing about

• Containing joiners: Define constraints that require joining on containing(), containedIn() or containingAny() logic in a far more scalable manner. For example, joining every two entities that share a tag.
• Java Platform Module System (JPMS) support: Optionally run with the modulepath instead of the classpath to improve code encapsulation. Learn more.

# Open source changes

We created Timefold to free the world of wasteful scheduling, not just to save OptaPlanner. Our open source solver is a critical part of that mission: Timefold Solver solves any scheduling problem, for free. We invest heavily in it, with a large, dedicated engineering team. It’s in production across the globe to schedule millions of activities every day.

As Timefold Solver grew, we expanded our offering beyond solving, into Explainability. Today, we’re restructuring the Solver editions accordingly, to better reflect how companies use it for commercial gain.

Starting with 2.0, Explainability moves to Timefold Solver Plus, a new paid edition. The score analysis and recommend assignment APIs are now part of that offering. This is a unique functionality which no other solver offers. It helps build trust and explains why a schedule looks the way it does. In the next few months, we will further expand the explainability features.

The new Plus edition gives growing teams access to more powerful features without jumping straight to Enterprise. We are offering a launch price until June 30th.

The open source edition can still solve any scheduling problem, for any constraint. It’s still free for commercial use. Still Apache License 2.0. Still fully tested, reliable and production-ready. We are expanding the solving features there too, as we’ve done for the last 20 years.

# Free licenses

To support scientific research and charity organizations, Timefold Solver Enterprise (including Plus) is now free for non-profits and academic use.

# Trial license

To verify the added value of Timefold Solver Plus and Enterprise, you can now easily download a free trial for 30 days.

# Upgrading from 1.x

Timefold Solver 2.0 is mostly backwards compatible with 1.x. All deprecated methods have been removed to create a cleaner API.

We've worked hard to make the upgrade as smooth as possible:

1. Upgrade automatically with our OpenRewrite recipe.
2. If you run into any compilation error, check the comprehensive migration guide that covers every change in detail.

Timefold Solver 1.x is maintained throughout 2026 with quarterly bug-fix and security releases so you can plan your migration accordingly. That being said, we recommend switching to 2.x as soon as possible. If you run into issues while upgrading, don’t hesitate to contact us and we'll work through it together.

# A note from the team

Building and maintaining a solver at this level of quality takes serious, ongoing investment. We're proud of what this community has built together, and we're committed to keeping Timefold Solver healthy for the long term.

Timefold Solver 2.0 is available now. Check out the documentation to get started today.

If you have questions, don't hesitate to reach out.