Forget about Machine Learning. Planning optimization is the most profitable AI technology on this planet.
The world is full of planning challenges, such as vehicle routing problems, maintenance scheduling and employee rostering. Find the quickest routes to visit n locations with k vehicles. Or assign shifts to employees, taking into account skills and availability. Few people realize how much AI algorithms improve those solutions. For example, when telco’s started using OptaPlanner to plan their fleet of technicians, many expected a driving time reduction of 1-2%. It was 25%. In some cases, that saves hundreds of millions of dollars and millions of kilograms of CO² emissions, every year.
In this session we’ll show you how to code a highschool timetabling application, with OptaPlanner. It will generate the perfect lesson schedule, for both students and teachers, taking into account hard and soft constraints. Then, we ‘ll ramp up to more complex applications, such as maintenance scheduling or vehicle routing, and how to deal with more challenging business requirements. OptaPlanner (Java, open source, apache license) is compatible with plain Java, Kotlin, Quarkus, Spring, Maven, Gradle, etc
Scheduled on Thursday from 16:30 to 17:20 (Europe/London) in Room B
Geoffrey De Smet is the lead of OptaPlanner (www.optaplanner.org), the open source AI constraint solver in Java that is used across the globe to automatically solve employee rostering, vehicle routing, task assignment, maintenance scheduling and other planning problems. He's an international speaker.