KieLive#15: OptaPlanner domain models and design patterns

In this live session, we'll learn how to properly choose your @PlanningVariable

Link to the presentation: http://red.ht/KieLive15

KieLive#15: OptaPlanner domain models and design patterns

Picking the right model for your first optimization problem is notoriously hard. Luckily it gets a lot easier the more practice you have. In this session, I’ll walk you through a number of OptaPlanner models and explain the motivation for the design of each model.

About the invited speaker:
Geoffrey De Smet is the founder and lead of OptaPlanner, the open source AI constraint solver in Java that is used across the globe for all kinds of planning and scheduling operations.

Transcript

1. Domain models Domain models and and design patterns design patterns by Geoffrey De Smet OptaPlanner lead
2. Announcements Announcements OptaPlanner Quick Starts repository github.com/kiegroup/optaplanner-quickstarts (https://github.com/kiegroup/optaplanner- quickstarts)
3. Announcements Announcements OptaPlanner Quick Starts repository Quick Starts Showcase github.com/kiegroup/optaplanner-quickstarts (https://github.com/kiegroup/optaplanner- quickstarts)
4. Announcements Announcements OptaPlanner Quick Starts repository Quick Starts Showcase DEMO github.com/kiegroup/optaplanner-quickstarts (https://github.com/kiegroup/optaplanner- quickstarts)
5. Why is modeling hard? (*) Why is modeling hard? (*)
6. Why is modeling hard? (*) Why is modeling hard? (*) (*) at least the rst few times
7. Given a text like this... School timetabling School timetabling Optimize a school timetable of lessons to assign teachers and students in the best room at the best time.
8. Given a text like this... School timetabling School timetabling Optimize a school timetable of lessons to assign teachers and students in the best room at the best time. Come up with a model like this...
10. Let's take it step by step... School timetabling School timetabling Optimize a school timetable of lessons to assign teachers and students in the best room at the best time.
11. What changes during planning? What changes during planning?
15. DEMO DEMO
16. What changes during planning? What changes during planning? The assigned timeslot of each lesson The assigned room of each lesson
18. What are the constraints? What are the constraints?
19. What are the constraints? What are the constraints? 1. Which hard constraints are build-in in our model?
20. What are the constraints? What are the constraints? 1. Which hard constraints are build-in in our model? 2. Which constraints affect our planning variables?
21. Constraints inventory Constraints inventory Each lesson must have one timeslot Each lesson must have one room No lessons in the same room together No teacher with lessons at the same time Students must be able to attend all lessons Use each teacher's time ef ciently Give students variety in subjects
22. Constraints inventory Constraints inventory Each lesson must have one timeslot (hard) Each lesson must have one room No lessons in the same room together No teacher with lessons at the same time Students must be able to attend all lessons Use each teacher's time ef ciently Give students variety in subjects
23. Constraints inventory Constraints inventory Each lesson must have one timeslot (hard) Each lesson must have one room (hard) No lessons in the same room together No teacher with lessons at the same time Students must be able to attend all lessons Use each teacher's time ef ciently Give students variety in subjects
24. Constraints inventory Constraints inventory Each lesson must have one timeslot (hard) Each lesson must have one room (hard) No lessons in the same room together (hard) No teacher with lessons at the same time Students must be able to attend all lessons Use each teacher's time ef ciently Give students variety in subjects
25. Constraints inventory Constraints inventory Each lesson must have one timeslot (hard) Each lesson must have one room (hard) No lessons in the same room together (hard) No teacher with lessons at the same time (hard) Students must be able to attend all lessons Use each teacher's time ef ciently Give students variety in subjects
26. Constraints inventory Constraints inventory Each lesson must have one timeslot (hard) Each lesson must have one room (hard) No lessons in the same room together (hard) No teacher with lessons at the same time (hard) Students must be able to attend all lessons (hard) Use each teacher's time ef ciently Give students variety in subjects
27. Constraints inventory Constraints inventory Each lesson must have one timeslot (hard) Each lesson must have one room (hard) No lessons in the same room together (hard) No teacher with lessons at the same time (hard) Students must be able to attend all lessons (hard) Use each teacher's time ef ciently (soft) Give students variety in subjects
28. Constraints inventory Constraints inventory Each lesson must have one timeslot (hard) Each lesson must have one room (hard) No lessons in the same room together (hard) No teacher with lessons at the same time (hard) Students must be able to attend all lessons (hard) Use each teacher's time ef ciently (soft) Give students variety in subjects (soft)
29. Which hard constraints are build-in Which hard constraints are build-in in our model? in our model?
30. Which hard constraints are build-in Which hard constraints are build-in in our model? in our model? Each lesson must have one timeslot (build-in hard)
31. Which hard constraints are build-in Which hard constraints are build-in in our model? in our model? Each lesson must have one timeslot (build-in hard) Each lesson must have one room (build-in hard)
33. Hard constraints (not build-in) Hard constraints (not build-in) Room con ict: No 2 lessons in the same room at the same time Teacher con ict: No 2 lessons for the same teacher at the same time Student con ict: No 2 lessons for the same student group at the same time
34. Hard constraints (not build-in) Hard constraints (not build-in) Room con ict: No 2 lessons in the same room at the same time Teacher con ict: No 2 lessons for the same teacher at the same time Student con ict: No 2 lessons for the same student group at the same time Formalize your constraints.
35. Soft constraints Soft constraints Teacher time ef ciently: No gap between teacher lessons Subject variety: No sequential lessons on the same subject
36. Some constraints affect the Some constraints affect the planning variables. planning variables. Most don't.
37. Some constraints affect the Some constraints affect the planning variables. planning variables. Most don't. Learn to tell them apart: Do these planning variables hinder any of the constraints?
39. Constraints that Constraints that don't affect the model don't affect the model Skill requirements and af nity Availability and unavailability Fairness and load balancing Time windows, ... (many more)
40. Constraints that Constraints that don't affect the model don't affect the model Skill requirements and af nity Availability and unavailability Fairness and load balancing Time windows, ... (many more) Most constraints do not affect the model!
41. The PlanningSolution is easy The PlanningSolution is easy
42. Modeling tips Modeling tips
52. The PlanningSolution is easy The PlanningSolution is easy to determine to determine
57. Exercises Exercises
67. Assigning to time Assigning to time
79. Shadow variables Shadow variables
92. Exercises Exercises
97. Getting started Getting started
98. Quick starts Quick starts github.com/kiegroup/optaplanner-quickstarts (https://github.com/kiegroup/optaplanner- quickstarts) $ git clone git@github.com:kiegroup/optaplanner-quickstarts.git ... $ cd optaplanner-quickstarts $ cd quarkus-school-timetabling $ mvn quarkus:dev ...
99. @GeoffreyDeSmet Q & A Q & A Homepage Slides User guide Feedback www.optaplanner.org (https://www.optapl www.optaplanner.org/learn/slides.html (https://www.optaplanner.org/learn/slides www.optaplanner.org/learn/documentatio (https://www.optaplanner.org/learn/docum @GeoffreyDeSmet (https://twitter.com/GeoffreyDeSmet)