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Chapter 10. Red Hat build of OptaPlanner on Spring Boot: a school timetable quick start guide

This guide walks you through the process of creating a Spring Boot application with OptaPlanner’s constraint solving artificial intelligence (AI). 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 the following hard and soft scheduling constraints:

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 in a single room.
A teacher prefers to teach sequential lessons and dislikes gaps between lessons.

Mathematically speaking, school timetabling is an NP-hard problem. That means it is difficult to scale. Simply iterating through all possible combinations with brute force would take millions of years for a non-trivial dataset, even on a supercomputer. Fortunately, AI constraint solvers such as OptaPlanner have advanced algorithms that deliver a near-optimal solution in a reasonable amount of time. What is considered to be a reasonable amount of time is subjective and depends on the goals of your problem.

Prerequisites

OpenJDK 11 or later is installed. Red Hat build of Open JDK is available from the Software Downloads page in the Red Hat Customer Portal (login required).
Apache Maven 3.6 or higher is installed. Maven is available from the Apache Maven Project website.
An IDE, such as IntelliJ IDEA, VSCode, Eclipse, or NetBeans is available.

10.1. Downloading and building the Spring Boot school timetable quick start

If you want to see a completed example of the school timetable project for Red Hat build of OptaPlanner with Spring Boot product, download the starter application from the Red Hat Customer Portal.

Procedure

Navigate to the Software Downloads page in the Red Hat Customer Portal (login required), and select the product and version from the drop-down options:
- Product: Process Automation Manager
- Version: 7.11
Download Red Hat Process Automation Manager 7.11.0 Kogito and OptaPlanner 8 Decision Services Quickstarts (rhpam-7.11.0-decision-services-quickstarts.zip).
Extract the rhpam-7.11.0-decision-services-quickstarts.zip file.
Download the Red Hat Process Automation Manager 7.11.0 Kogito and OptaPlanner 8 Decision Services Maven Repositroy (rhpam-7.11.0-kogito-maven-repository.zip).
Extract the rhpam-7.11.0-kogito-maven-repository.zip file.
Copy the contents of the rhpam-7.11.0-kogito-maven-repository/maven-repository subdirectory into the ~/.m2/repository directory.
Navigate to the optaplanner-quickstarts-8.5.0.Final-redhat-00004/spring-boot-school-timetabling directory.
Enter the following command to build the Spring Boot school timetabling project:
```
mvn clean install -DskipTests
```
To build the Spring Boot school timetabling project, enter the following command:
```
mvn spring-boot:run -DskipTests
```
To view the project, enter the following URL in a web browser:
```
http://localhost:8080/
```

10.2. Model the domain objects

The goal of the Red Hat build of OptaPlanner timetable project is to assign each lesson to a time slot and a room. To do this, add three classes, Timeslot, Lesson, and Room, as shown in the following diagram:

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. In this example, 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. There is no need for continuous planning. A timeslot is called a problem fact because no Timeslot instances change during solving. Such classes do not require any OptaPlanner-specific annotations.

Room

The Room class represents a location where lessons are taught, for example, Room A or Room B. In this example, all rooms are without capacity limits and they can accommodate all lessons.

Room instances do not change during solving so Room is also a problem fact.

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 each 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.

Procedure

Create the src/main/java/com/example/domain/Timeslot.java class:

package com.example.domain;

import java.time.DayOfWeek;
import java.time.LocalTime;

public class Timeslot {

    private DayOfWeek dayOfWeek;
    private LocalTime startTime;
    private LocalTime endTime;

    private Timeslot() {
    }

    public Timeslot(DayOfWeek dayOfWeek, LocalTime startTime, LocalTime endTime) {
        this.dayOfWeek = dayOfWeek;
        this.startTime = startTime;
        this.endTime = endTime;
    }

    @Override
    public String toString() {
        return dayOfWeek + " " + startTime.toString();
    }

    // ********************************
    // Getters and setters
    // ********************************

    public DayOfWeek getDayOfWeek() {
        return dayOfWeek;
    }

    public LocalTime getStartTime() {
        return startTime;
    }

    public LocalTime getEndTime() {
        return endTime;
    }

}

Notice the toString() method keeps the output short so it is easier to read OptaPlanner’s DEBUG or TRACE log, as shown later.

Create the src/main/java/com/example/domain/Room.java class:

package com.example.domain;

public class Room {

    private String name;

    private Room() {
    }

    public Room(String name) {
        this.name = name;
    }

    @Override
    public String toString() {
        return name;
    }

    // ********************************
    // Getters and setters
    // ********************************

    public String getName() {
        return name;
    }

}

Create the src/main/java/com/example/domain/Lesson.java class:

package com.example.domain;

import org.optaplanner.core.api.domain.entity.PlanningEntity;
import org.optaplanner.core.api.domain.variable.PlanningVariable;

@PlanningEntity
public class Lesson {

    private Long id;

    private String subject;
    private String teacher;
    private String studentGroup;

    @PlanningVariable(valueRangeProviderRefs = "timeslotRange")
    private Timeslot timeslot;

    @PlanningVariable(valueRangeProviderRefs = "roomRange")
    private Room room;

    private Lesson() {
    }

    public Lesson(Long id, String subject, String teacher, String studentGroup) {
        this.id = id;
        this.subject = subject;
        this.teacher = teacher;
        this.studentGroup = studentGroup;
    }

    @Override
    public String toString() {
        return subject + "(" + id + ")";
    }

    // ********************************
    // Getters and setters
    // ********************************

    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;
    }

}

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 valueRangeProviderRefs property to connect to a value range provider that provides a List<Timeslot> to pick from. See Section 10.4, “Gather the domain objects in a planning solution” for information about value range providers.

The room field also has an @PlanningVariable annotation for the same reasons.

10.3. Define the constraints and calculate the score

When solving a problem, a score represents the quality of a specific solution. The higher the score the better. Red Hat build of 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 the timetable example 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 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> {

    @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 "complete" implementation
        return HardSoftScore.of(hardScore, softScore);
    }

}

Unfortunately, this solution 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.

A better solution is to create a src/main/java/com/example/solver/TimeTableConstraintProvider.java class to perform incremental score calculation. This class uses OptaPlanner’s ConstraintStream API which is inspired by Java 8 Streams and SQL. The ConstraintProvider scales an order of magnitude better than the EasyScoreCalculator: O(n) instead of O(n²).

Procedure

Create the following src/main/java/com/example/solver/TimeTableConstraintProvider.java class:

package com.example.solver;

import com.example.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 "complete" implementation
        };
    }

    private Constraint roomConflict(ConstraintFactory constraintFactory) {
        // A room can accommodate at most one lesson at the same time.

        // Select a lesson ...
        return constraintFactory.from(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("Room conflict", HardSoftScore.ONE_HARD);
    }

    private Constraint teacherConflict(ConstraintFactory constraintFactory) {
        // A teacher can teach at most one lesson at the same time.
        return constraintFactory.from(Lesson.class)
                .join(Lesson.class,
                        Joiners.equal(Lesson::getTimeslot),
                        Joiners.equal(Lesson::getTeacher),
                        Joiners.lessThan(Lesson::getId))
                .penalize("Teacher conflict", HardSoftScore.ONE_HARD);
    }

    private Constraint studentGroupConflict(ConstraintFactory constraintFactory) {
        // A student can attend at most one lesson at the same time.
        return constraintFactory.from(Lesson.class)
                .join(Lesson.class,
                        Joiners.equal(Lesson::getTimeslot),
                        Joiners.equal(Lesson::getStudentGroup),
                        Joiners.lessThan(Lesson::getId))
                .penalize("Student group conflict", HardSoftScore.ONE_HARD);
    }

}

10.4. Gather the domain objects in a planning solution

A TimeTable instance 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.

The TimeTable class has an @PlanningSolution annotation, so Red Hat build of 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 and room fields are typically still null, so unassigned. They are planning variables.
  - The other fields, such as subject, teacher and studentGroup, are filled in. These fields are problem properties.

However, this class is also the output of the solution:

A lessonList field for which each Lesson instance has non-null timeslot and room fields after solving
A score field that represents the quality of the output solution, for example, 0hard/-5soft

Procedure

Create the src/main/java/com/example/domain/TimeTable.java class:

package com.example.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(id = "timeslotRange")
    @ProblemFactCollectionProperty
    private List<Timeslot> timeslotList;

    @ValueRangeProvider(id = "roomRange")
    @ProblemFactCollectionProperty
    private List<Room> roomList;

    @PlanningEntityCollectionProperty
    private List<Lesson> lessonList;

    @PlanningScore
    private HardSoftScore score;

    private TimeTable() {
    }

    public TimeTable(List<Timeslot> timeslotList, List<Room> roomList,
            List<Lesson> lessonList) {
        this.timeslotList = timeslotList;
        this.roomList = roomList;
        this.lessonList = lessonList;
    }

    // ********************************
    // Getters and setters
    // ********************************

    public List<Timeslot> getTimeslotList() {
        return timeslotList;
    }

    public List<Room> getRoomList() {
        return roomList;
    }

    public List<Lesson> getLessonList() {
        return lessonList;
    }

    public HardSoftScore getScore() {
        return score;
    }

}

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 those two, by matching the id with the valueRangeProviderRefs of the @PlanningVariable in the Lesson.

Following the same logic, the roomList field also has an @ValueRangeProvider annotation.

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.

10.5. Create the Timetable 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, which runs solvers in a separate thread pool and can solve multiple datasets in parallel.

Procedure

Create the src/main/java/com/example/solver/TimeTableController.java class:

package com.example.solver;

import java.util.UUID;
import java.util.concurrent.ExecutionException;

import com.example.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;
    }

}

In this example, the initial implementation waits for the solver to finish, which can still cause an HTTP timeout. The complete implementation avoids HTTP timeouts much more elegantly.

10.6. Set the solver termination time

If your planning application does not have a termination setting or a termination event, it theoretically runs forever and in reality eventually causes an HTTP timeout error. To prevent this from occurring, use the optaplanner.solver.termination.spent-limit parameter to specify the length of time after which the application terminates. In most applications, set the time to at least five minutes (5m). However, in the Timetable example, limit the solving time to five second, which is short enough to avoid the HTTP timeout.

Procedure

Create the src/main/resources/application.properties file with the following content:

quarkus.optaplanner.solver.termination.spent-limit=5s

10.7. Make the application executable

After you complete the Red Hat build of OptaPlanner Spring Boot timetable project, package everything into a single executable JAR file driven by a standard Java main() method.

Prerequisites

You have a completed OptaPlanner Spring Boot timetable project.

Procedure

Create the TimeTableSpringBootApp.java class with the following content:

package com.example;

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);
    }

}

Replace the src/main/java/com/example/DemoApplication.java class created by Spring Initializr with the TimeTableSpringBootApp.java class.
Run the TimeTableSpringBootApp.java class as the main class of a regular Java application.

10.7.1. Try the timetable application

After you start the Red Hat build of OptaPlanner Spring Boot timetable application, you can test the REST service with any REST client that you want. This example uses the Linux curl command to send a POST request.

Prerequisites

The OptaPlanner Spring Boot timetable application is running.

Procedure

Enter the following command:

$ 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, the termination spent time defined in 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 the 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).

10.7.2. Test the application

A good application includes test coverage. This example tests the Timetable Red Hat build of OptaPlanner Spring Boot application. It uses a JUnit test to generate a test dataset and send it to the TimeTableController to solve.

Procedure

Create the src/test/java/com/example/solver/TimeTableControllerTest.java class with the following content:

package com.example.solver;

import java.time.DayOfWeek;
import java.time.LocalTime;
import java.util.ArrayList;
import java.util.List;

import com.example.domain.Lesson;
import com.example.domain.Room;
import com.example.domain.TimeTable;
import com.example.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 = {
        "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 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 overwrites the solver termination 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 systems. However, it does not run a millisecond longer than it strictly must, even on fast systems.

10.7.3. Logging

After you complete the Red Hat build of OptaPlanner Spring Boot timetable application, you can use logging information to help you fine-tune the constraints in the ConstraintProvider. Review the score calculation speed in the info log file to assess the impact of changes to your constraints. Run the application in debug mode to show every step that your application takes or use trace logging to log every step and every move.

Procedure

Run the timetable application for a fixed amount of time, for example, five minutes.
Review the score calculation speed in the log file as shown in the following example:
```
... Solving ended: ..., score calculation speed (29455/sec), ...
```
Change a constraint, run the planning application again for the same amount of time, and review the score calculation speed recorded in the log file.

Run the application in debug mode to log every step:

To run debug mode from the command line, use the -D system property.

To change logging in the application.properties file, add the following line to that file:

logging.level.org.optaplanner=debug

The following example shows output in the log file in debug mode:

... 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 for each step.

10.8. Add Database and UI integration

After you create the Red Hat build of OptaPlanner application example with Spring Boot, add database and UI integration.

Prerequisite

You have created the OptaPlanner Spring Boot timetable example.

Procedure

Create Java Persistence API (JPA) repositories for Timeslot, Room, and Lesson. For information about creating JPA repositories, see Accessing Data with JPA on the Spring website.
Expose the JPA repositories through REST. For information about exposing the repositories, see Accessing JPA Data with REST on the Spring website.
Build a TimeTableRepository facade to read and write a TimeTable in a single transaction.

Adjust the TimeTableController as shown in the following example:

package com.example.solver;

import com.example.domain.TimeTable;
import com.example.persistence.TimeTableRepository;
import org.optaplanner.core.api.score.ScoreManager;
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 ScoreManager<TimeTable> scoreManager;

    // 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);
        scoreManager.updateScore(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, this code handles only one TimeTable instance, but it is straightforward to enable multi-tenancy and handle multiple TimeTable instances of different high schools in parallel.

The getTimeTable() method returns the latest timetable from the database. It uses the ScoreManager (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 the SolverManager.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.

Now that the solve() method returns immediately, adjust the TimeTableControllerTest as shown in the following example:

package com.example.solver;

import com.example.domain.Lesson;
import com.example.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 systems and doesn't randomly fail on slow systems.
            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());
    }

}

Poll for the latest solution until the solver finishes solving.
To visualize the time table, build an attractive web UI on top of these REST methods.

Select Your Language

Chapter 10. Red Hat build of OptaPlanner on Spring Boot: a school timetable quick start guide

10.1. Downloading and building the Spring Boot school timetable quick start

10.2. Model the domain objects

10.3. Define the constraints and calculate the score

10.4. Gather the domain objects in a planning solution

10.5. Create the Timetable service

10.6. Set the solver termination time

10.7. Make the application executable

10.7.1. Try the timetable application

10.7.2. Test the application

10.7.3. Logging

10.8. Add Database and UI integration

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Chapter 10. Red Hat build of OptaPlanner on Spring Boot: a school timetable quick start guide

10.1. Downloading and building the Spring Boot school timetable quick start

10.2. Model the domain objects

10.3. Define the constraints and calculate the score

10.4. Gather the domain objects in a planning solution

10.5. Create the Timetable service

10.6. Set the solver termination time

10.7. Make the application executable

10.7.1. Try the timetable application

10.7.2. Test the application

10.7.3. Logging

10.8. Add Database and UI integration

Quick Links

Help

Site Info

Related Sites

Systems Status

About

Red Hat legal and privacy links

Red Hat legal and privacy links