Geoffrey De Smet
Source code: https://github.com/quarkusio/quarkus-quickstarts/tree/master/optaplanner-quickstart
Guide: https://quarkus.io/guides/optaplanner
OptaPlanner homepage: https://www.optaplanner.org
Follow me on twitter: https://twitter.com/GeoffreyDeSmet
Shows how to program a REST application that optimizes a school timetable according to hard and soft constraints with constraint solving Artificial Intelligence algorithms (such as metaheuristics, local search and construction heuristics). It’s implemented in Java with Quarkus and OptaPlanner and build with Maven. Under the hood it also uses Hibernate, H2, RestEasy and Kogito-Drools, all of which are open source. It briefly touches upon a few other planning optimizaton problems, such as the vehicle routing problem, job shop scheduling, equipment scheduling, bin packing and employee shift rostering. The resulting work can run both on HotSpot and GraalVM, the latter by building with -Dnative. It can run on-premise and in the cloud, including OpenShift/Kubernetes: see the quarkus guides for that.
Source
Thnk u a lot <3
Nice. Shame about the low video quality. It's tough to read the code…
I loved it! It would be awesome if you would upload frequently, that was very interesting
How quickly OptaPlanner evolves : my documentation (on v. 7.29.0) showed up to be already outdated… chapter 6 (Constraint stream score calculation) had a big update in the meantime (refering to documentation v. 7.32.0, in the meantime already at 7.35.0 so to see)… All stuff to work on. Thank you for your ongoing work on OptaPlanner.
(dankbare groeten vanuit België)
Thanks a lot it is very useful!