The timefold-quickstarts repository serves as a collection of practical starting points for developers learning to use Timefold Solver, an AI constraint solver designed for Java and Kotlin applications. The repository demonstrates how to apply constraint programming and optimization techniques to real-world planning problems across diverse domains including logistics, scheduling, and resource allocation.
The repository contains fifteen distinct use case implementations, each showcasing different solver concepts and optimization patterns. Vehicle routing examples demonstrate chained planning variables and shadow variables for finding efficient delivery routes while respecting vehicle capacity and time window constraints. Employee scheduling quickstarts illustrate load balancing techniques for assigning shifts to workers based on availability and skill requirements. Maintenance scheduling implementations show how to use TimeGrain and variable listeners to optimize crew assignments over time. Additional use cases cover food packaging line optimization, order picking workflows, school timetabling, facility location problems, conference scheduling, hospital bed allocation, flight crew assignments, meeting scheduling, task assignment, project job scheduling, sports league scheduling, and tournament scheduling. Each use case includes documented constraints and runnable implementations.
The quickstarts are built primarily with Java using Maven and Quarkus frameworks, with some examples also provided in Kotlin. Most implementations include rudimentary user interfaces to illustrate the optimization problems visually, though the repository explicitly notes that Timefold Solver itself is a library without built-in UI components. The implementations are intentionally designed as starting points and inspiration rather than production-ready solutions.
According to GitGenius activity tracking, the repository has seen consistent engagement with a median issue and pull request response latency of zero hours, indicating active maintenance. Across forty-seven tracked items, the mean response latency was 1992.9 hours, reflecting the repository's overall responsiveness. The most frequently applied issue labels are bug with fourteen occurrences, enhancement with eight, and good first issue with five, suggesting the project maintains a welcoming stance toward new contributors. The primary contributors tracked by GitGenius are triceo with fifty-four events, TomCools with twenty-five events, and zepfred with twenty-five events, demonstrating concentrated but collaborative maintenance.
The repository is classified across multiple categories including quickstarts, tutorials, examples, guides, and AI tools, reflecting its educational purpose. It shares contributors with related repositories including timefoldai/timefold-solver, the core solver library, as well as quarkusio/quarkus and containers/ramalama, indicating integration within a broader ecosystem of Java and containerization tools.
The repository includes a legal notice documenting that it was forked from OptaPlanner Quickstarts on April 20, 2023, and represents a derivative work maintaining the original Apache-2.0 licensing while noting that every source file has been modified. This heritage connects the quickstarts to the established OptaPlanner project while establishing Timefold as an independent continuation of constraint programming optimization tools.
