Introduction

Every organization faces planning problems: providing products or services with a limited set of constrained resources (employees, assets, time, and money). Timefold Solver’s PlanningAI optimizes these problems to do more business with fewer resources using Constraint Satisfaction Programming.

This documentation provides guidance on using our open-source solver to build custom models from scratch. For common planning problems, we also offer ready-made models that can be seamlessly integrated via our REST API.

Explore our documentation and available models here

Timefold Solver is a lightweight, embeddable constraint satisfaction engine which optimizes planning problems. Example usecases include:

useCaseOverview
Figure 1. Timefold Solver’s use cases include vehicle routing, employee scheduling, rostering, bin packing, and equipment scheduling.

Timefold Solver is 100% pure JavaTM and runs on Java 17 or higher. It integrates very easily with other JavaTM, Python, and other technologies. Timefold Solver works on any Java Virtual Machine and is compatible with the major JVM languages and all major platforms. It also supports Kotlin and Python.

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