Indictments are back, and better than before! One of the frequent comments we have received with Timefold Solver 2.0 was that we should not have removed indictments - we listened, and they are now back, as part of Score Analysis. Find out more about the new indictments in our documentation.

The recently introduced service module has received a lot of love, as we continue to lay the groundwork for being able to host your own models on our platform. Speaking of which - have you seen Timefold's AI-powered modeling assistant?

And of course, what Solver release would this be if it didn't bring numerous performance improvements and bugfixes.

Changelog

🚀 Features

• Add indictment support to Bavet's Node Network (#2528)
• (Service) Add execution profile to generate thread dumps on OOMs (#2710)
• (Service) Implement multi transport types for the same dataset (#2579)
• (Service) Add verbose-logging execution profile (#2709)
• (Service) Create profile set custom seed (#2665)

🐛 Fixes

• Clone solution for first solution and solver started events (#2732)
• Keep variable metamodel comparison consistent with equality
• Update all unassigned values when multiple were unassigned (#2689)
• (Service) Generate timefold-build.properties in the module's build directory (#2629)
• (Service) Polish map service API (#2683)

🔄️ Changes

• (Performance) Avoid clear() on a large hash map
• (Performance) Walk declarative successors by list index (#2735)
• (Performance) Size the Gizmo clone map after the previous clone (#2729)
• (Performance) Resolve declarative graph reactions once per variable
• (Performance) Cache the location index when the distance matrix is filled first (#2693)
• (Performance) Fixed graph update once (#2673)
• (Performance) Less PositionInList allocations (#2681)

Contributors

We'd like to thank the following people for their contributions, in no particular order:

• Christopher Chianelli (@Christopher-Chianelli)
• Cristiano Nicolai (@cristianonicolai)
• Diogo Ferreira (@diogodanielsoaresferreira)
• Frederico Gonçalves (@zepfred)
• Jenne De Bleser (@jennedebleser)
• Jurriaan Persyn (@oemebamo)
• Lars Beckmann (@larsbeck)
• Lukáš Petrovický (@triceo)
• Maciej Swiderski (@mswiderski)
• Marek Winkler (@winklerm)
• Radovan Synek (@rsynek)
• Sumit Kumar Singh (@Sumit-Ks1)
• Tom Cools (@TomCools)
• Vikas Prasad (@vikas-prasad-cx)
• @fodzal

Timefold Solver Community Edition is an open source project, and you are more than welcome to contribute as well! For more, see Contributing.

Timefold also offers an Enterprise edition of the solver, which includes additional features such as explainability, the ability to scale out to the biggest datasets, and enterprise-grade support. Find out more about the different editions.

How to use Timefold Solver

To see Timefold Solver in action, check out the quickstarts.

With Maven or Gradle, add the ai.timefold.solver : timefold-solver-core : 2.8.0 dependency in your pom.xml to get started.

You can also import the Timefold Solver Bom (ai.timefold.solver : timefold-solver-bom : 2.8.0) to avoid duplicating version numbers when adding other Timefold Solver dependencies later on.

Additional notes

The changelog and the list of contributors above are automatically generated. It excludes contributions to certain areas of the repository, such as CI and build automation. This is done for the sake of brevity and to make the user-facing changes stand out more.