Artificial Intelligence on Quarkus:I love it when an OptaPlan comes
summary
Claim: planning optimization beats ML for scheduling and routing, with a cited case delivering 25% driving-time reduction and millions of kg CO₂ saved per year. Demonstration builds a high‑school timetabler on Quarkus + OptaPlanner, mapping entities/variables (Lesson with room and timeslot planning variables), adding hard constraints: room/teacher/student conflicts, and scoring soft objectives for compact schedules. Implementation uses solveAndListen with SolverManager to persist best solutions and Quarkus dev mode for sub‑second live reloads.
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chapters (8)
- 0:00Introduction to AI planning
- 1:19Live coding demo setup
- 9:00Real-world planning problems
- 15:15Quarkus and OptaPlanner integration
- 25:55Quarkus Dev mode benefits
- 31:26Adding OptaPlanner to domain
- 40:07Solving with constraints
- 47:28Soft constraints and resources
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