Spring Boot Java quick start
This guide walks you through the process of creating a Spring Boot application with OptaPlanner's constraint solving Artificial Intelligence (AI).
1. What you will build
You will build a REST application that optimizes a school timetable for students and teachers:
Your service will assign Lesson
instances to Timeslot
and Room
instances automatically
by using AI to adhere to hard and soft scheduling constraints, such as the following examples:
-
A room can have at most one lesson at the same time.
-
A teacher can teach at most one lesson at the same time.
-
A student can attend at most one lesson at the same time.
-
A teacher prefers to teach all lessons in the same room.
-
A teacher prefers to teach sequential lessons and dislikes gaps between lessons.
-
A student dislikes sequential lessons on the same subject.
Mathematically speaking, school timetabling is an NP-hard problem. This means it is difficult to scale. Simply brute force iterating through all possible combinations takes millions of years for a non-trivial data set, even on a supercomputer. Luckily, AI constraint solvers such as OptaPlanner have advanced algorithms that deliver a near-optimal solution in a reasonable amount of time.
2. Solution source code
Follow the instructions in the next sections to create the application step by step (recommended).
Alternatively, you can also skip right to the completed example:
-
Clone the Git repository:
$ git clone https://github.com/kiegroup/optaplanner-quickstarts
or download an archive.
-
Find the solution in the
technology
directory and run it (see its README file).
3. Prerequisites
To complete this guide, you need:
-
JDK 11+ with
JAVA_HOME
configured appropriately -
Apache Maven 3.8.1+ or Gradle 4+
-
An IDE, such as IntelliJ IDEA, VSCode or Eclipse
4. The build file and the dependencies
Create a Spring Boot application with the following dependencies:
-
Spring Web (
spring-boot-starter-web
) -
OptaPlanner (
optaplanner-spring-boot-starter
)
If you choose Maven, your pom.xml
file has the following content:
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-parent</artifactId>
<version>3.0.7</version>
</parent>
<groupId>org.acme</groupId>
<artifactId>optaplanner-spring-boot-school-timetabling-quickstart</artifactId>
<version>1.0-SNAPSHOT</version>
<properties>
<java.version>11</java.version>
<version.org.optaplanner>9.44.0.Final</version.org.optaplanner>
</properties>
<dependencyManagement>
<dependencies>
<dependency>
<groupId>org.optaplanner</groupId>
<artifactId>optaplanner-bom</artifactId>
<version>${version.org.optaplanner}</version>
<type>pom</type>
<scope>import</scope>
</dependency>
</dependencies>
</dependencyManagement>
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-rest</artifactId>
</dependency>
<dependency>
<groupId>org.optaplanner</groupId>
<artifactId>optaplanner-spring-boot-starter</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.optaplanner</groupId>
<artifactId>optaplanner-test</artifactId>
<scope>test</scope>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-maven-plugin</artifactId>
</plugin>
</plugins>
</build>
</project>
On the other hand, in Gradle, your build.gradle
file has this content:
plugins {
id "org.springframework.boot" version "3.0.7"
id "io.spring.dependency-management" version "1.0.11.RELEASE"
id "java"
}
def optaplannerVersion = "9.44.0.Final"
group = "org.acme"
version = "1.0-SNAPSHOT"
sourceCompatibility = "11"
repositories {
mavenCentral()
}
dependencies {
implementation "org.springframework.boot:spring-boot-starter-web"
implementation "org.springframework.boot:spring-boot-starter-data-rest"
testImplementation("org.springframework.boot:spring-boot-starter-test")
implementation platform("org.optaplanner:optaplanner-bom:${optaplannerVersion}")
implementation "org.optaplanner:optaplanner-spring-boot-starter"
testImplementation("org.optaplanner:optaplanner-test")
}
test {
useJUnitPlatform()
}
5. Model the domain objects
Your goal is to assign each lesson to a time slot and a room. You will create these classes:
5.1. Timeslot
The Timeslot
class represents a time interval when lessons are taught,
for example, Monday 10:30 - 11:30
or Tuesday 13:30 - 14:30
.
For simplicity’s sake, all time slots have the same duration
and there are no time slots during lunch or other breaks.
A time slot has no date, because a high school schedule just repeats every week. So there is no need for continuous planning.
Create the src/main/java/org/acme/schooltimetabling/domain/Timeslot.java
class:
package org.acme.schooltimetabling.domain;
import java.time.DayOfWeek;
import java.time.LocalTime;
public class Timeslot {
private DayOfWeek dayOfWeek;
private LocalTime startTime;
private LocalTime endTime;
public Timeslot() {
}
public Timeslot(DayOfWeek dayOfWeek, LocalTime startTime, LocalTime endTime) {
this.dayOfWeek = dayOfWeek;
this.startTime = startTime;
this.endTime = endTime;
}
public DayOfWeek getDayOfWeek() {
return dayOfWeek;
}
public LocalTime getStartTime() {
return startTime;
}
public LocalTime getEndTime() {
return endTime;
}
@Override
public String toString() {
return dayOfWeek + " " + startTime;
}
}
Because no Timeslot
instances change during solving, a Timeslot
is called a problem fact.
Such classes do not require any OptaPlanner specific annotations.
Notice the toString()
method keeps the output short,
so it is easier to read OptaPlanner’s DEBUG
or TRACE
log, as shown later.
5.2. Room
The Room
class represents a location where lessons are taught,
for example, Room A
or Room B
.
For simplicity’s sake, all rooms are without capacity limits
and they can accommodate all lessons.
Create the src/main/java/org/acme/schooltimetabling/domain/Room.java
class:
package org.acme.schooltimetabling.domain;
public class Room {
private String name;
public Room() {
}
public Room(String name) {
this.name = name;
}
public String getName() {
return name;
}
@Override
public String toString() {
return name;
}
}
Room
instances do not change during solving, so Room
is also a problem fact.
5.3. Lesson
During a lesson, represented by the Lesson
class,
a teacher teaches a subject to a group of students,
for example, Math by A.Turing for 9th grade
or Chemistry by M.Curie for 10th grade
.
If a subject is taught multiple times per week by the same teacher to the same student group,
there are multiple Lesson
instances that are only distinguishable by id
.
For example, the 9th grade has six math lessons a week.
During solving, OptaPlanner changes the timeslot
and room
fields of the Lesson
class,
to assign each lesson to a time slot and a room.
Because OptaPlanner changes these fields, Lesson
is a planning entity:
Most of the fields in the previous diagram contain input data, except for the orange fields:
A lesson’s timeslot
and room
fields are unassigned (null
) in the input data
and assigned (not null
) in the output data.
OptaPlanner changes these fields during solving.
Such fields are called planning variables.
In order for OptaPlanner to recognize them,
both the timeslot
and room
fields require an @PlanningVariable
annotation.
Their containing class, Lesson
, requires an @PlanningEntity
annotation.
Create the src/main/java/org/acme/schooltimetabling/domain/Lesson.java
class:
package org.acme.schooltimetabling.domain;
import org.optaplanner.core.api.domain.entity.PlanningEntity;
import org.optaplanner.core.api.domain.lookup.PlanningId;
import org.optaplanner.core.api.domain.variable.PlanningVariable;
@PlanningEntity
public class Lesson {
@PlanningId
private Long id;
private String subject;
private String teacher;
private String studentGroup;
@PlanningVariable
private Timeslot timeslot;
@PlanningVariable
private Room room;
public Lesson() {
}
public Lesson(Long id, String subject, String teacher, String studentGroup) {
this.id = id;
this.subject = subject;
this.teacher = teacher;
this.studentGroup = studentGroup;
}
public Long getId() {
return id;
}
public String getSubject() {
return subject;
}
public String getTeacher() {
return teacher;
}
public String getStudentGroup() {
return studentGroup;
}
public Timeslot getTimeslot() {
return timeslot;
}
public void setTimeslot(Timeslot timeslot) {
this.timeslot = timeslot;
}
public Room getRoom() {
return room;
}
public void setRoom(Room room) {
this.room = room;
}
@Override
public String toString() {
return subject + "(" + id + ")";
}
}
The Lesson
class has an @PlanningEntity
annotation,
so OptaPlanner knows that this class changes during solving
because it contains one or more planning variables.
The timeslot
field has an @PlanningVariable
annotation,
so OptaPlanner knows that it can change its value.
In order to find potential Timeslot
instances to assign to this field,
OptaPlanner uses the variable type to connect to a value range provider
that provides a List<Timeslot>
to pick from.
The room
field also has an @PlanningVariable
annotation, for the same reasons.
Determining the |
6. Define the constraints and calculate the score
A score represents the quality of a specific solution. The higher the better. OptaPlanner looks for the best solution, which is the solution with the highest score found in the available time. It might be the optimal solution.
Because this use case has hard and soft constraints,
use the HardSoftScore
class to represent the score:
-
Hard constraints must not be broken. For example: A room can have at most one lesson at the same time.
-
Soft constraints should not be broken. For example: A teacher prefers to teach in a single room.
Hard constraints are weighted against other hard constraints. Soft constraints are weighted too, against other soft constraints. Hard constraints always outweigh soft constraints, regardless of their respective weights.
To calculate the score, you could implement an EasyScoreCalculator
class:
public class TimeTableEasyScoreCalculator implements EasyScoreCalculator<TimeTable, HardSoftScore> {
@Override
public HardSoftScore calculateScore(TimeTable timeTable) {
List<Lesson> lessonList = timeTable.getLessonList();
int hardScore = 0;
for (Lesson a : lessonList) {
for (Lesson b : lessonList) {
if (a.getTimeslot() != null && a.getTimeslot().equals(b.getTimeslot())
&& a.getId() < b.getId()) {
// A room can accommodate at most one lesson at the same time.
if (a.getRoom() != null && a.getRoom().equals(b.getRoom())) {
hardScore--;
}
// A teacher can teach at most one lesson at the same time.
if (a.getTeacher().equals(b.getTeacher())) {
hardScore--;
}
// A student can attend at most one lesson at the same time.
if (a.getStudentGroup().equals(b.getStudentGroup())) {
hardScore--;
}
}
}
}
int softScore = 0;
// Soft constraints are only implemented in the optaplanner-quickstarts code
return HardSoftScore.of(hardScore, softScore);
}
}
Unfortunately that does not scale well, because it is non-incremental: every time a lesson is assigned to a different time slot or room, all lessons are re-evaluated to calculate the new score.
Instead, create a src/main/java/org/acme/schooltimetabling/solver/TimeTableConstraintProvider.java
class
to perform incremental score calculation.
It uses OptaPlanner’s ConstraintStream API which is inspired by Java Streams and SQL:
package org.acme.schooltimetabling.solver;
import org.acme.schooltimetabling.domain.Lesson;
import org.optaplanner.core.api.score.buildin.hardsoft.HardSoftScore;
import org.optaplanner.core.api.score.stream.Constraint;
import org.optaplanner.core.api.score.stream.ConstraintFactory;
import org.optaplanner.core.api.score.stream.ConstraintProvider;
import org.optaplanner.core.api.score.stream.Joiners;
public class TimeTableConstraintProvider implements ConstraintProvider {
@Override
public Constraint[] defineConstraints(ConstraintFactory constraintFactory) {
return new Constraint[] {
// Hard constraints
roomConflict(constraintFactory),
teacherConflict(constraintFactory),
studentGroupConflict(constraintFactory),
// Soft constraints are only implemented in the optaplanner-quickstarts code
};
}
private Constraint roomConflict(ConstraintFactory constraintFactory) {
// A room can accommodate at most one lesson at the same time.
// Select a lesson ...
return constraintFactory
.forEach(Lesson.class)
// ... and pair it with another lesson ...
.join(Lesson.class,
// ... in the same timeslot ...
Joiners.equal(Lesson::getTimeslot),
// ... in the same room ...
Joiners.equal(Lesson::getRoom),
// ... and the pair is unique (different id, no reverse pairs) ...
Joiners.lessThan(Lesson::getId))
// ... then penalize each pair with a hard weight.
.penalize(HardSoftScore.ONE_HARD)
.asConstraint("Room conflict");
}
private Constraint teacherConflict(ConstraintFactory constraintFactory) {
// A teacher can teach at most one lesson at the same time.
return constraintFactory.forEach(Lesson.class)
.join(Lesson.class,
Joiners.equal(Lesson::getTimeslot),
Joiners.equal(Lesson::getTeacher),
Joiners.lessThan(Lesson::getId))
.penalize(HardSoftScore.ONE_HARD)
.asConstraint("Teacher conflict");
}
private Constraint studentGroupConflict(ConstraintFactory constraintFactory) {
// A student can attend at most one lesson at the same time.
return constraintFactory.forEach(Lesson.class)
.join(Lesson.class,
Joiners.equal(Lesson::getTimeslot),
Joiners.equal(Lesson::getStudentGroup),
Joiners.lessThan(Lesson::getId))
.penalize(HardSoftScore.ONE_HARD)
.asConstraint("Student group conflict");
}
}
The ConstraintProvider
scales an order of magnitude better than the EasyScoreCalculator
: O(n) instead of O(n²).
7. Gather the domain objects in a planning solution
A TimeTable
wraps all Timeslot
, Room
, and Lesson
instances of a single dataset.
Furthermore, because it contains all lessons, each with a specific planning variable state,
it is a planning solution and it has a score:
-
If lessons are still unassigned, then it is an uninitialized solution, for example, a solution with the score
-4init/0hard/0soft
. -
If it breaks hard constraints, then it is an infeasible solution, for example, a solution with the score
-2hard/-3soft
. -
If it adheres to all hard constraints, then it is a feasible solution, for example, a solution with the score
0hard/-7soft
.
Create the src/main/java/org/acme/schooltimetabling/domain/TimeTable.java
class:
package org.acme.schooltimetabling.domain;
import java.util.List;
import org.optaplanner.core.api.domain.solution.PlanningEntityCollectionProperty;
import org.optaplanner.core.api.domain.solution.PlanningScore;
import org.optaplanner.core.api.domain.solution.PlanningSolution;
import org.optaplanner.core.api.domain.solution.ProblemFactCollectionProperty;
import org.optaplanner.core.api.domain.valuerange.ValueRangeProvider;
import org.optaplanner.core.api.score.buildin.hardsoft.HardSoftScore;
@PlanningSolution
public class TimeTable {
@ValueRangeProvider
@ProblemFactCollectionProperty
private List<Timeslot> timeslotList;
@ValueRangeProvider
@ProblemFactCollectionProperty
private List<Room> roomList;
@PlanningEntityCollectionProperty
private List<Lesson> lessonList;
@PlanningScore
private HardSoftScore score;
public TimeTable() {
}
public TimeTable(List<Timeslot> timeslotList, List<Room> roomList, List<Lesson> lessonList) {
this.timeslotList = timeslotList;
this.roomList = roomList;
this.lessonList = lessonList;
}
public List<Timeslot> getTimeslotList() {
return timeslotList;
}
public List<Room> getRoomList() {
return roomList;
}
public List<Lesson> getLessonList() {
return lessonList;
}
public HardSoftScore getScore() {
return score;
}
}
The TimeTable
class has an @PlanningSolution
annotation,
so OptaPlanner knows that this class contains all of the input and output data.
Specifically, this class is the input of the problem:
-
A
timeslotList
field with all time slots-
This is a list of problem facts, because they do not change during solving.
-
-
A
roomList
field with all rooms-
This is a list of problem facts, because they do not change during solving.
-
-
A
lessonList
field with all lessons-
This is a list of planning entities, because they change during solving.
-
Of each
Lesson
:-
The values of the
timeslot
androom
fields are typically stillnull
, so unassigned. They are planning variables. -
The other fields, such as
subject
,teacher
andstudentGroup
, are filled in. These fields are problem properties.
-
-
However, this class is also the output of the solution:
-
A
lessonList
field for which eachLesson
instance has non-nulltimeslot
androom
fields after solving -
A
score
field that represents the quality of the output solution, for example,0hard/-5soft
7.1. The value range providers
The timeslotList
field is a value range provider.
It holds the Timeslot
instances which OptaPlanner can pick from to assign to the timeslot
field of Lesson
instances.
The timeslotList
field has an @ValueRangeProvider
annotation to connect the @PlanningVariable
with the @ValueRangeProvider
,
by matching the type of the planning variable with the type returned by the value range provider.
Following the same logic, the roomList
field also has an @ValueRangeProvider
annotation.
7.2. The problem fact and planning entity properties
Furthermore, OptaPlanner needs to know which Lesson
instances it can change
as well as how to retrieve the Timeslot
and Room
instances used for score calculation
by your TimeTableConstraintProvider
.
The timeslotList
and roomList
fields have an @ProblemFactCollectionProperty
annotation,
so your TimeTableConstraintProvider
can select from those instances.
The lessonList
has an @PlanningEntityCollectionProperty
annotation,
so OptaPlanner can change them during solving
and your TimeTableConstraintProvider
can select from those too.
8. Create the solver service
Now you are ready to put everything together and create a REST service.
But solving planning problems on REST threads causes HTTP timeout issues.
Therefore, the Spring Boot starter injects a SolverManager
instance,
which runs solvers in a separate thread pool
and can solve multiple datasets in parallel.
Create the src/main/java/org/acme/schooltimetabling/rest/TimeTableController.java
class:
package org.acme.schooltimetabling.rest;
import java.util.UUID;
import java.util.concurrent.ExecutionException;
import org.acme.schooltimetabling.domain.TimeTable;
import org.optaplanner.core.api.solver.SolverJob;
import org.optaplanner.core.api.solver.SolverManager;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.PostMapping;
import org.springframework.web.bind.annotation.RequestBody;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;
@RestController
@RequestMapping("/timeTable")
public class TimeTableController {
@Autowired
private SolverManager<TimeTable, UUID> solverManager;
@PostMapping("/solve")
public TimeTable solve(@RequestBody TimeTable problem) {
UUID problemId = UUID.randomUUID();
// Submit the problem to start solving
SolverJob<TimeTable, UUID> solverJob = solverManager.solve(problemId, problem);
TimeTable solution;
try {
// Wait until the solving ends
solution = solverJob.getFinalBestSolution();
} catch (InterruptedException | ExecutionException e) {
throw new IllegalStateException("Solving failed.", e);
}
return solution;
}
}
For simplicity’s sake, this initial implementation waits for the solver to finish, which can still cause an HTTP timeout. The complete implementation avoids HTTP timeouts much more elegantly.
9. Set the termination time
Without a termination setting or a terminationEarly()
event, the solver runs forever.
To avoid that, limit the solving time to five seconds.
That is short enough to avoid the HTTP timeout.
Create the src/main/resources/application.properties
file:
# The solver runs only for 5 seconds to avoid a HTTP timeout in this simple implementation.
# It's recommended to run for at least 5 minutes ("5m") otherwise.
optaplanner.solver.termination.spent-limit=5s
OptaPlanner returns the best solution found in the available termination time. Due to the nature of NP-hard problems, the best solution might not be optimal, especially for larger datasets. Increase the termination time to potentially find a better solution.
10. Make the application executable
Package everything into a single executable JAR file driven by a standard Java main()
method:
Replace the DemoApplication.java
class created by Spring Initializr
with the src/main/java/org/acme/schooltimetabling/TimeTableSpringBootApp.java
class:
package org.acme.schooltimetabling;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
@SpringBootApplication
public class TimeTableSpringBootApp {
public static void main(String[] args) {
SpringApplication.run(TimeTableSpringBootApp.class, args);
}
}
Run that TimeTableSpringBootApp
class as the main class of a normal Java application.
10.1. Try the application
Now that the application is running, you can test the REST service.
You can use any REST client you wish.
The following example uses the Linux command curl
to send a POST request:
$ curl -i -X POST http://localhost:8080/timeTable/solve -H "Content-Type:application/json" -d '{"timeslotList":[{"dayOfWeek":"MONDAY","startTime":"08:30:00","endTime":"09:30:00"},{"dayOfWeek":"MONDAY","startTime":"09:30:00","endTime":"10:30:00"}],"roomList":[{"name":"Room A"},{"name":"Room B"}],"lessonList":[{"id":1,"subject":"Math","teacher":"A. Turing","studentGroup":"9th grade"},{"id":2,"subject":"Chemistry","teacher":"M. Curie","studentGroup":"9th grade"},{"id":3,"subject":"French","teacher":"M. Curie","studentGroup":"10th grade"},{"id":4,"subject":"History","teacher":"I. Jones","studentGroup":"10th grade"}]}'
After about five seconds, according to the termination spent time defined in your application.properties
,
the service returns an output similar to the following example:
HTTP/1.1 200
Content-Type: application/json
...
{"timeslotList":...,"roomList":...,"lessonList":[{"id":1,"subject":"Math","teacher":"A. Turing","studentGroup":"9th grade","timeslot":{"dayOfWeek":"MONDAY","startTime":"08:30:00","endTime":"09:30:00"},"room":{"name":"Room A"}},{"id":2,"subject":"Chemistry","teacher":"M. Curie","studentGroup":"9th grade","timeslot":{"dayOfWeek":"MONDAY","startTime":"09:30:00","endTime":"10:30:00"},"room":{"name":"Room A"}},{"id":3,"subject":"French","teacher":"M. Curie","studentGroup":"10th grade","timeslot":{"dayOfWeek":"MONDAY","startTime":"08:30:00","endTime":"09:30:00"},"room":{"name":"Room B"}},{"id":4,"subject":"History","teacher":"I. Jones","studentGroup":"10th grade","timeslot":{"dayOfWeek":"MONDAY","startTime":"09:30:00","endTime":"10:30:00"},"room":{"name":"Room B"}}],"score":"0hard/0soft"}
Notice that your application assigned all four lessons to one of the two time slots and one of the two rooms. Also notice that it conforms to all hard constraints. For example, M. Curie’s two lessons are in different time slots.
On the server side, the info
log shows what OptaPlanner did in those five seconds:
... Solving started: time spent (33), best score (-8init/0hard/0soft), environment mode (REPRODUCIBLE), random (JDK with seed 0).
... Construction Heuristic phase (0) ended: time spent (73), best score (0hard/0soft), score calculation speed (459/sec), step total (4).
... Local Search phase (1) ended: time spent (5000), best score (0hard/0soft), score calculation speed (28949/sec), step total (28398).
... Solving ended: time spent (5000), best score (0hard/0soft), score calculation speed (28524/sec), phase total (2), environment mode (REPRODUCIBLE).
10.2. Test the application
A good application includes test coverage.
10.2.1. Test the constraints
To test each constraint in isolation, use a ConstraintVerifier
in unit tests.
It tests each constraint’s corner cases in isolation from the other tests,
which lowers maintenance when adding a new constraint with proper test coverage.
Add a optaplanner-test
dependency in your pom.xml
:
<dependency>
<groupId>org.optaplanner</groupId>
<artifactId>optaplanner-test</artifactId>
<scope>test</scope>
</dependency>
Create the src/test/java/org/acme/schooltimetabling/solver/TimeTableConstraintProviderTest.java
class:
package org.acme.schooltimetabling.solver;
import java.time.DayOfWeek;
import java.time.LocalTime;
import javax.inject.Inject;
import org.acme.schooltimetabling.domain.Lesson;
import org.acme.schooltimetabling.domain.Room;
import org.acme.schooltimetabling.domain.TimeTable;
import org.acme.schooltimetabling.domain.Timeslot;
import org.junit.jupiter.api.Test;
import org.optaplanner.test.api.score.stream.ConstraintVerifier;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;
@SpringBootTest
class TimeTableConstraintProviderTest {
private static final Room ROOM = new Room("Room1");
private static final Timeslot TIMESLOT1 = new Timeslot(DayOfWeek.MONDAY, LocalTime.of(9,0), LocalTime.NOON);
private static final Timeslot TIMESLOT2 = new Timeslot(DayOfWeek.TUESDAY, LocalTime.of(9,0), LocalTime.NOON);
@Autowired
ConstraintVerifier<TimeTableConstraintProvider, TimeTable> constraintVerifier;
@Test
void roomConflict() {
Lesson firstLesson = new Lesson(1, "Subject1", "Teacher1", "Group1");
Lesson conflictingLesson = new Lesson(2, "Subject2", "Teacher2", "Group2");
Lesson nonConflictingLesson = new Lesson(3, "Subject3", "Teacher3", "Group3");
firstLesson.setRoom(ROOM);
firstLesson.setTimeslot(TIMESLOT1);
conflictingLesson.setRoom(ROOM);
conflictingLesson.setTimeslot(TIMESLOT1);
nonConflictingLesson.setRoom(ROOM);
nonConflictingLesson.setTimeslot(TIMESLOT2);
constraintVerifier.verifyThat(TimeTableConstraintProvider::roomConflict)
.given(firstLesson, conflictingLesson, nonConflictingLesson)
.penalizesBy(1);
}
}
This test verifies that the constraint TimeTableConstraintProvider::roomConflict
,
when given three lessons in the same room, where two lessons have the same timeslot,
it penalizes with a match weight of 1
.
So with a constraint weight of 10hard
it would reduce the score by -10hard
.
Notice how ConstraintVerifier
ignores the constraint weight during testing - even
if those constraint weights are hard coded in the ConstraintProvider
- because
constraints weights change regularly before going into production.
This way, constraint weight tweaking does not break the unit tests.
10.2.2. Test the solver
In a JUnit test, generate a test dataset and send it to the TimeTableController
to solve.
Create the src/test/java/org/acme/schooltimetabling/rest/TimeTableControllerTest.java
class:
package org.acme.schooltimetabling.rest;
import java.time.DayOfWeek;
import java.time.LocalTime;
import java.util.ArrayList;
import java.util.List;
import org.acme.schooltimetabling.domain.Lesson;
import org.acme.schooltimetabling.domain.Room;
import org.acme.schooltimetabling.domain.TimeTable;
import org.acme.schooltimetabling.domain.Timeslot;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.api.Timeout;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;
import static org.junit.jupiter.api.Assertions.assertFalse;
import static org.junit.jupiter.api.Assertions.assertNotNull;
import static org.junit.jupiter.api.Assertions.assertTrue;
@SpringBootTest(properties = {
// Effectively disable spent-time termination in favor of the best-score-limit
"optaplanner.solver.termination.spent-limit=1h",
"optaplanner.solver.termination.best-score-limit=0hard/*soft"})
public class TimeTableControllerTest {
@Autowired
private TimeTableController timeTableController;
@Test
@Timeout(600_000)
public void solve() {
TimeTable problem = generateProblem();
TimeTable solution = timeTableController.solve(problem);
assertFalse(solution.getLessonList().isEmpty());
for (Lesson lesson : solution.getLessonList()) {
assertNotNull(lesson.getTimeslot());
assertNotNull(lesson.getRoom());
}
assertTrue(solution.getScore().isFeasible());
}
private TimeTable generateProblem() {
List<Timeslot> timeslotList = new ArrayList<>();
timeslotList.add(new Timeslot(DayOfWeek.MONDAY, LocalTime.of(8, 30), LocalTime.of(9, 30)));
timeslotList.add(new Timeslot(DayOfWeek.MONDAY, LocalTime.of(9, 30), LocalTime.of(10, 30)));
timeslotList.add(new Timeslot(DayOfWeek.MONDAY, LocalTime.of(10, 30), LocalTime.of(11, 30)));
timeslotList.add(new Timeslot(DayOfWeek.MONDAY, LocalTime.of(13, 30), LocalTime.of(14, 30)));
timeslotList.add(new Timeslot(DayOfWeek.MONDAY, LocalTime.of(14, 30), LocalTime.of(15, 30)));
List<Room> roomList = new ArrayList<>();
roomList.add(new Room("Room A"));
roomList.add(new Room("Room B"));
roomList.add(new Room("Room C"));
List<Lesson> lessonList = new ArrayList<>();
lessonList.add(new Lesson(101L, "Math", "B. May", "9th grade"));
lessonList.add(new Lesson(102L, "Physics", "M. Curie", "9th grade"));
lessonList.add(new Lesson(103L, "Geography", "M. Polo", "9th grade"));
lessonList.add(new Lesson(104L, "English", "I. Jones", "9th grade"));
lessonList.add(new Lesson(105L, "Spanish", "P. Cruz", "9th grade"));
lessonList.add(new Lesson(201L, "Math", "B. May", "10th grade"));
lessonList.add(new Lesson(202L, "Chemistry", "M. Curie", "10th grade"));
lessonList.add(new Lesson(203L, "History", "I. Jones", "10th grade"));
lessonList.add(new Lesson(204L, "English", "P. Cruz", "10th grade"));
lessonList.add(new Lesson(205L, "French", "M. Curie", "10th grade"));
return new TimeTable(timeslotList, roomList, lessonList);
}
}
This test verifies that after solving, all lessons are assigned to a time slot and a room. It also verifies that it found a feasible solution (no hard constraints broken).
Normally, the solver finds a feasible solution in less than 200 milliseconds.
Notice how the @SpringBootTest
annotation’s properties
property overwrites the solver termination during tests
to terminate as soon as a feasible solution (0hard/*soft
) is found.
This avoids hard coding a solver time, because the unit test might run on arbitrary hardware.
This approach ensures that the test runs long enough to find a feasible solution, even on slow machines.
But it does not run a millisecond longer than it strictly must, even on fast machines.
10.3. Logging
When adding constraints in your ConstraintProvider
,
keep an eye on the score calculation speed in the info
log,
after solving for the same amount of time, to assess the performance impact:
... Solving ended: ..., score calculation speed (29455/sec), ...
To understand how OptaPlanner is solving your problem internally,
change the logging in the application.properties
file or with a -D
system property:
logging.level.org.optaplanner=debug
Use debug
logging to show every step:
... Solving started: time spent (67), best score (-20init/0hard/0soft), environment mode (REPRODUCIBLE), random (JDK with seed 0).
... CH step (0), time spent (128), score (-18init/0hard/0soft), selected move count (15), picked move ([Math(101) {null -> Room A}, Math(101) {null -> MONDAY 08:30}]).
... CH step (1), time spent (145), score (-16init/0hard/0soft), selected move count (15), picked move ([Physics(102) {null -> Room A}, Physics(102) {null -> MONDAY 09:30}]).
...
Use trace
logging to show every step and every move per step.
11. Summary
Congratulations! You have just developed a Spring application with OptaPlanner!
12. Further improvements: Database and UI integration
Now try adding database and UI integration:
-
Create JPA repositories for
Timeslot
,Room
, andLesson
. -
Build a
TimeTableRepository
facade to read and write aTimeTable
instance in a single transaction. -
Adjust the
TimeTableController
accordingly:package org.acme.schooltimetabling.rest; import org.acme.schooltimetabling.domain.TimeTable; import org.acme.schooltimetabling.persistence.TimeTableRepository; import org.optaplanner.core.api.solver.SolutionManager; import org.optaplanner.core.api.solver.SolverManager; import org.optaplanner.core.api.solver.SolverStatus; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.web.bind.annotation.GetMapping; import org.springframework.web.bind.annotation.PostMapping; import org.springframework.web.bind.annotation.RequestMapping; import org.springframework.web.bind.annotation.RestController; @RestController @RequestMapping("/timeTable") public class TimeTableController { @Autowired private TimeTableRepository timeTableRepository; @Autowired private SolverManager<TimeTable, Long> solverManager; @Autowired private SolutionManager<TimeTable, HardSoftScore> solutionManager; // To try, GET http://localhost:8080/timeTable @GetMapping() public TimeTable getTimeTable() { // Get the solver status before loading the solution // to avoid the race condition that the solver terminates between them SolverStatus solverStatus = getSolverStatus(); TimeTable solution = timeTableRepository.findById(TimeTableRepository.SINGLETON_TIME_TABLE_ID); solutionManager.update(solution); // Sets the score solution.setSolverStatus(solverStatus); return solution; } @PostMapping("/solve") public void solve() { solverManager.solveAndListen(TimeTableRepository.SINGLETON_TIME_TABLE_ID, timeTableRepository::findById, timeTableRepository::save); } public SolverStatus getSolverStatus() { return solverManager.getSolverStatus(TimeTableRepository.SINGLETON_TIME_TABLE_ID); } @PostMapping("/stopSolving") public void stopSolving() { solverManager.terminateEarly(TimeTableRepository.SINGLETON_TIME_TABLE_ID); } }
For simplicity’s sake, this code handles only one
TimeTable
instance, but it is straightforward to enable multi-tenancy and handle multipleTimeTable
instances of different high schools in parallel.The
getTimeTable()
method returns the latest timetable from the database. It uses theSolutionManager
(which is automatically injected) to calculate the score of that timetable, so the UI can show the score.The
solve()
method starts a job to solve the current timetable and store the time slot and room assignments in the database. It uses theSolverManager.solveAndListen()
method to listen to intermediate best solutions and update the database accordingly. This enables the UI to show progress while the backend is still solving. -
Adjust the
TimeTableControllerTest
instance accordingly, now that thesolve()
method returns immediately. Poll for the latest solution until the solver finishes solving:package org.acme.schooltimetabling.rest; import org.acme.schooltimetabling.domain.Lesson; import org.acme.schooltimetabling.domain.TimeTable; import org.junit.jupiter.api.Test; import org.junit.jupiter.api.Timeout; import org.optaplanner.core.api.solver.SolverStatus; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.boot.test.context.SpringBootTest; import static org.junit.jupiter.api.Assertions.assertFalse; import static org.junit.jupiter.api.Assertions.assertNotNull; import static org.junit.jupiter.api.Assertions.assertTrue; @SpringBootTest(properties = { "optaplanner.solver.termination.spent-limit=1h", // Effectively disable this termination in favor of the best-score-limit "optaplanner.solver.termination.best-score-limit=0hard/*soft"}) public class TimeTableControllerTest { @Autowired private TimeTableController timeTableController; @Test @Timeout(600_000) public void solveDemoDataUntilFeasible() throws InterruptedException { timeTableController.solve(); TimeTable timeTable = timeTableController.getTimeTable(); while (timeTable.getSolverStatus() != SolverStatus.NOT_SOLVING) { // Quick polling (not a Test Thread Sleep anti-pattern) // Test is still fast on fast machines and doesn't randomly fail on slow machines. Thread.sleep(20L); timeTable = timeTableController.getTimeTable(); } assertFalse(timeTable.getLessonList().isEmpty()); for (Lesson lesson : timeTable.getLessonList()) { assertNotNull(lesson.getTimeslot()); assertNotNull(lesson.getRoom()); } assertTrue(timeTable.getScore().isFeasible()); } }
-
Build an attractive web UI on top of these REST methods to visualize the timetable.
Take a look at the quickstart source code to see how this all turns out.