This repository contains quickstarts for Timefold Solver, an AI constraint solver for Java, Python, and Kotlin. It shows different use cases and basic implementations to get you started on your PlanningAI journey.
| Use Case |
Notable Solver Concepts |
|---|---|
| 🚚 Vehicle Routing | Chained Through Time, Shadow Variables |
| 🧑💼 Employee Scheduling | Load Balancing |
| 🛠️ Maintenance Scheduling | TimeGrain, Shadow Variable, Variable Listener |
| 📦 Food Packaging | Chained Through Time, Shadow Variables, Pinning |
| 🛒 Order Picking | Chained Planning Variable, Shadow Variables |
| 🏫 School Timetabling | Timeslot |
| 🏭 Facility Location Problem | Shadow Variable |
| 🎤 Conference Scheduling | Timeslot, Justifications |
| 🛏️ Bed Allocation Scheduling | Allows Unassigned |
| 🛫 Flight Crew Scheduling | |
| 👥 Meeting Scheduling | TimeGrain |
| ✅ Task Assigning | Bendable Score, Chained Through Time, Allows Unassigned |
| 📆 Project Job Scheduling | Shadow Variables, Variable Listener, Strenght Comparator |
| 🏆 Sports League Scheduling | Consecutive Sequences |
| 🏅 Tournament Scheduling | Pinning, Load Balancing |
Note
The implementations in this repository serve as a starting point and/or inspiration when creating your own application. Timefold Solver is a library and does not include a UI. To illustrate these use cases a rudimentary UI is included in these quickstarts.
Find the most efficient routes for vehicles to reach visits, considering vehicle capacity and time windows when visits are available. Sometimes also called "CVRPTW".
- Run quarkus-vehicle-routing (Java, Maven, Quarkus)
- Run python-vehicle-routing (Python, FastAPI)
Tip
Schedule shifts to employees, accounting for employee availability and shift skill requirements.
- Run quarkus-employee-scheduling (Java, Maven, Quarkus)
- Run python-employee-scheduling (Python, FastAPI)
Tip
Schedule maintenance jobs to crews over time to reduce both premature and overdue maintenance.
- Run quarkus-maintenance-scheduling (Java, Maven, Quarkus)
Schedule food packaging orders to manufacturing lines to minimize downtime and fulfill all orders on time.
- Run quarkus-food-packaging (Java, Maven, Quarkus)
Generate an optimal picking plan for completing a set of orders.
- Run quarkus-order-picking (Java, Maven, Quarkus)
Assign lessons to timeslots and rooms to produce a better schedule for teachers and students.
- Run quarkus-school-timetabling (Java, Maven or Gradle, Quarkus)
- Run spring-boot-school-timetabling (Java, Maven or Gradle, Spring Boot)
- Run kotlin-quarkus-school-timetabling (Kotlin, Maven, Quarkus)
- Run python-school-timetabling (Python, FastAPI)
Without a UI:
- Run hello-world-school-timetabling (Java, Maven or Gradle)
Pick the best geographical locations for new stores, distribution centers, COVID test centers, or telecom masts.
- Run quarkus-facility-location (Java, Maven, Quarkus)
Assign conference talks to timeslots and rooms to produce a better schedule for speakers.
- Run quarkus-conference-scheduling (Java, Maven, Quarkus)
Assign beds to patient stays to produce a better schedule for hospitals.
- Run quarkus-bed-allocation-scheduling (Java, Maven, Quarkus)
Assign crew to flights to produce a better schedule for flight assignments.
- Run quarkus-flight-crew-scheduling (Java, Maven, Quarkus)
- Run python-flight-crew-scheduling (Python, FastAPI)
Assign timeslots and rooms for meetings to produce a better schedule.
- Run quarkus-meeting-scheduling (Java, Maven, Quarkus)
Assign employees to tasks to produce a better plan for task assignments.
- Run quarkus-task-assigning (Java, Maven, Quarkus)
Assign jobs for execution to produce a better schedule for project job allocations.
- Run quarkus-project-job-scheduling (Java, Maven, Quarkus)
Assign rounds to matches to produce a better schedule for league matches.
- Run quarkus-sports-league-scheduling (Java, Maven, Quarkus)
- Run python-sports-league-scheduling (Python, FastAPI)
Tournament Scheduling service assigning teams to tournament matches.
- Run quarkus-tournament-scheduling (Java, Maven, Quarkus)
- Run python-tournament-scheduling (Python, FastAPI)
Timefold Quickstarts was forked on 20 April 2023 from OptaPlanner Quickstarts, which was entirely Apache-2.0 licensed (a permissive license).
Timefold Quickstarts is a derivative work of OptaPlanner Quickstarts, which includes copyrights of the original creator, Red Hat Inc., affiliates, and contributors, that were all entirely licensed under the Apache-2.0 license. Every source file has been modified.