For our final release of 2023, we’ve prepared some exciting things!

Featured Update - Recommended Fit API, a game-changer for appointment scheduling.

• Use case: Imagine you are an operator on a phone line, or an AI chatbot. A customer asks you for an appointment with a sales representative. Where do you put that appointment in their busy calendar?
• Timefold Solver now provides superfast sub-second response times, while still taking all your constraints into account!
• Result: Operators can receive a list of appointment choices, ranked from best fit to worst, for informed decision-making. Ensuring they can make an informed choice that has the least potential to disrupt the schedule as a whole.

Other Enhancements:

• Constraint Streams now simplify solving constraints with sequences of indefinite length.
• Debugging score corruptions is now easier.
• Various other improvements and bug fixes to enhance overall user experience.

Changelog

🚀 Features

• Introduce the Recommended Fit API, closes #432
• Promote consecutive sequence collector to public API, closes #426
• Add constraint weight to ScoreAnalysis, closes #416
• Report missing before/after calls on undo corruption, closes #433
• Report shadow variables that differ after recalculating from scratch when undo corruption occurs, closes #430
• Identify Solver version and edition in Benchmarker, Spring and Quarkus, closes #411

🐛 Fixes

• Shadow entities should be annotated with @PlanningEntityCollectionProperty, closes #445
• Example app logo transparency
• Support repeatable annotations like ShadowVariable in Quarkus

🧰 Tasks

• Replace ready/due time by min/max start/end time, closes #436 #438

📝 Documentation

• Move development section from user guide to Github CONTRIBUTING
• Restructure chapters on using and configuring solver

Contributors

We'd like to thank the following people for their contributions:

• Christopher Chianelli
• Geoffrey De Smet
• Lukáš Petrovický (@triceo)
• Pieter De Schepper
• Radovan Synek
• dependabot[bot] (@dependabot[bot])

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

Should your business need to scale to truly massive data sets or require enterprise-grade support, check out Timefold Solver Enterprise Edition.

How to use Timefold Solver

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

With Maven or Gradle, just add the ai.timefold.solver : timefold-solver-core : 1.5.0 dependency in your pom.xml to get started.

You can also import the Timefold Solver Bom (ai.timefold.solver : timefold-solver-bom : 1.5.0) 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. They exclude 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.