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.

Want to dive right into it? Follow our Quickstart Example to tackle your first planning problem in minutes.

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

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

Timefold Solver is 100% pure Java^TM and runs on Java 17 or higher. It integrates very easily with other Java^TM, 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.

Follow the Quickstart Example to tackle your first planning problem.
Learn about some important concepts used in the realm of PlanningAI.

Introduction

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