feat: Adding VRP quickstart documentation (#623)

This pull request adds documentation for VRP quickstart using Quarkus.
The structure of the document is based on existing quickstart documents.

Author: zepfred

docs/src/modules/ROOT/images/quickstart/vehicle-routing/vehicleRouteScreenshot.png

@@ -4,3 +4,4 @@
 :hello-world-java-quickstart-url: https://github.com/TimefoldAI/timefold-quickstarts/tree/stable/hello-world
 :spring-boot-quickstart-url: https://github.com/TimefoldAI/timefold-quickstarts/tree/stable/technology/java-spring-boot
 :quarkus-quickstart-url: https://github.com/TimefoldAI/timefold-quickstarts/tree/stable/use-cases/school-timetabling
+:vrp-quickstart-url: https://github.com/TimefoldAI/timefold-quickstarts/tree/stable/use-cases/vehicle-routing

docs/src/modules/ROOT/images/quickstart/vehicle-routing/vehicleRoutingClassDiagramAnnotated.png

@@ -11,3 +11,5 @@ include::hello-world/hello-world-quickstart.adoc[leveloffset=+1]
 include::quarkus/quarkus-quickstart.adoc[leveloffset=+1]
 
 include::spring-boot/spring-boot-quickstart.adoc[leveloffset=+1]
+
+include::vrp-quarkus/vrp-quarkus-quickstart.adoc[leveloffset=+1]

docs/src/modules/ROOT/images/quickstart/vehicle-routing/vehicleRoutingClassDiagramPure.png

@@ -0,0 +1,281 @@
+= Define the constraints and calculate the score
+:imagesdir: ../..
+
+A _score_ represents the quality of a specific solution.
+The higher the better.
+Timefold Solver 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: _The vehicle capacity must not be exceeded._
+* Soft constraints should not be broken.
+For example: _The sum total of travel time._
+
+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:
+
+[tabs]
+====
+Java::
++
+--
+[source,java]
+----
+package org.acme.vehiclerouting.solver;
+
+import java.util.List;
+
+import ai.timefold.solver.core.api.score.buildin.hardsoftlong.HardSoftLongScore;
+import ai.timefold.solver.core.api.score.calculator.EasyScoreCalculator;
+
+import org.acme.vehiclerouting.domain.Vehicle;
+import org.acme.vehiclerouting.domain.VehicleRoutePlan;
+import org.acme.vehiclerouting.domain.Visit;
+
+public class VehicleRoutingEasyScoreCalculator implements EasyScoreCalculator<VehicleRoutePlan, HardSoftLongScore> {
+    @Override
+    public HardSoftLongScore calculateScore(VehicleRoutePlan vehicleRoutePlan) {
+
+        List<Vehicle> vehicleList = vehicleRoutePlan.getVehicles();
+
+        int hardScore = 0;
+        int softScore = 0;
+        for (Vehicle vehicle : vehicleList) {
+
+            // The demand exceeds the capacity
+            if (vehicle.getVisits() != null && vehicle.getTotalDemand() > vehicle.getCapacity()) {
+                hardScore -= vehicle.getTotalDemand() - vehicle.getCapacity();
+            }
+
+            // Max end-time not met
+            if (vehicle.getVisits() != null) {
+                for (Visit visit: vehicle.getVisits()) {
+                    if (visit.isServiceFinishedAfterMaxEndTime()) {
+                        hardScore -= visit.getServiceFinishedDelayInMinutes();
+                    }
+                }
+            }
+
+            softScore -= (int) vehicle.getTotalDrivingTimeSeconds();
+        }
+
+        return HardSoftLongScore.of(hardScore, softScore);
+    }
+}
+----
+--
+
+Kotlin::
++
+--
+[source,kotlin]
+----
+package org.acme.vehiclerouting.solver;
+
+import ai.timefold.solver.core.api.score.buildin.hardsoftlong.HardSoftLongScore
+import ai.timefold.solver.core.api.score.calculator.EasyScoreCalculator
+
+import org.acme.vehiclerouting.domain.Vehicle
+import org.acme.vehiclerouting.domain.VehicleRoutePlan
+
+class VehicleRoutingEasyScoreCalculator :
+    EasyScoreCalculator<VehicleRoutePlan, HardSoftLongScore> {
+    override fun calculateScore(vehicleRoutePlan: VehicleRoutePlan): HardSoftLongScore {
+        val vehicleList: List<Vehicle> = vehicleRoutePlan.vehicles!!
+
+        var hardScore = 0
+        var softScore = 0
+        for (vehicle in vehicleList) {
+            // The demand exceeds the capacity
+
+            if (vehicle.visits != null && vehicle.totalDemand > vehicle.capacity) {
+                hardScore -= (vehicle.totalDemand - vehicle.capacity).toInt()
+            }
+
+            // Max end-time not met
+            if (vehicle.visits != null) {
+                for (visit in vehicle.visits!!) {
+                    if (visit.isServiceFinishedAfterMaxEndTime) {
+                        hardScore -= visit.serviceFinishedDelayInMinutes.toInt()
+                    }
+                }
+            }
+
+            softScore -= vehicle.totalDrivingTimeSeconds.toInt()
+        }
+
+        return HardSoftLongScore.of(hardScore.toLong(), softScore.toLong())
+    }
+}
+----
+--
+====
+
+
+Unfortunately **that does not scale well**, because it is non-incremental:
+every time a visit is scheduled to a different vehicle,
+all visits are re-evaluated to calculate the new score.
+
+Instead, create a `VehicleRoutingConstraintProvider` class
+to perform incremental score calculation.
+It uses Timefold Solver's xref:constraints-and-score/score-calculation.adoc[Constraint Streams API]
+which is inspired by Java Streams and SQL:
+
+[tabs]
+====
+Java::
++
+--
+Create a `src/main/java/org/acme/vehiclerouting/solver/VehicleRoutingConstraintProvider.java` class:
+
+[source,java]
+----
+package org.acme.vehiclerouting.solver;
+
+import ai.timefold.solver.core.api.score.buildin.hardsoftlong.HardSoftLongScore;
+import ai.timefold.solver.core.api.score.stream.Constraint;
+import ai.timefold.solver.core.api.score.stream.ConstraintFactory;
+import ai.timefold.solver.core.api.score.stream.ConstraintProvider;
+
+import org.acme.vehiclerouting.domain.Visit;
+import org.acme.vehiclerouting.domain.Vehicle;
+import org.acme.vehiclerouting.solver.justifications.MinimizeTravelTimeJustification;
+import org.acme.vehiclerouting.solver.justifications.ServiceFinishedAfterMaxEndTimeJustification;
+import org.acme.vehiclerouting.solver.justifications.VehicleCapacityJustification;
+
+public class VehicleRoutingConstraintProvider implements ConstraintProvider {
+
+    public static final String VEHICLE_CAPACITY = "vehicleCapacity";
+    public static final String SERVICE_FINISHED_AFTER_MAX_END_TIME = "serviceFinishedAfterMaxEndTime";
+    public static final String MINIMIZE_TRAVEL_TIME = "minimizeTravelTime";
+
+    @Override
+    public Constraint[] defineConstraints(ConstraintFactory factory) {
+        return new Constraint[] {
+                vehicleCapacity(factory),
+                serviceFinishedAfterMaxEndTime(factory),
+                minimizeTravelTime(factory)
+        };
+    }
+
+    protected Constraint vehicleCapacity(ConstraintFactory factory) {
+        return factory.forEach(Vehicle.class)
+                .filter(vehicle -> vehicle.getTotalDemand() > vehicle.getCapacity())
+                .penalizeLong(HardSoftLongScore.ONE_HARD,
+                        vehicle -> vehicle.getTotalDemand() - vehicle.getCapacity())
+                .justifyWith((vehicle, score) -> new VehicleCapacityJustification(vehicle.getId(), vehicle.getTotalDemand(),
+                        vehicle.getCapacity()))
+                .asConstraint(VEHICLE_CAPACITY);
+    }
+
+    protected Constraint serviceFinishedAfterMaxEndTime(ConstraintFactory factory) {
+        return factory.forEach(Visit.class)
+                .filter(Visit::isServiceFinishedAfterMaxEndTime)
+                .penalizeLong(HardSoftLongScore.ONE_HARD,
+                        Visit::getServiceFinishedDelayInMinutes)
+                .justifyWith((visit, score) -> new ServiceFinishedAfterMaxEndTimeJustification(visit.getId(),
+                        visit.getServiceFinishedDelayInMinutes()))
+                .asConstraint(SERVICE_FINISHED_AFTER_MAX_END_TIME);
+    }
+
+    protected Constraint minimizeTravelTime(ConstraintFactory factory) {
+        return factory.forEach(Vehicle.class)
+                .penalizeLong(HardSoftLongScore.ONE_SOFT,
+                        Vehicle::getTotalDrivingTimeSeconds)
+                .justifyWith((vehicle, score) -> new MinimizeTravelTimeJustification(vehicle.getId(),
+                        vehicle.getTotalDrivingTimeSeconds()))
+                .asConstraint(MINIMIZE_TRAVEL_TIME);
+    }
+}
+
+----
+--
+
+Kotlin::
++
+--
+Create a `src/main/kotlin/org/acme/vehiclerouting/solver/VehicleRoutingConstraintProvider.kt` class:
+
+[source,kotlin]
+----
+package org.acme.vehiclerouting.solver
+
+import ai.timefold.solver.core.api.score.buildin.hardsoftlong.HardSoftLongScore
+import ai.timefold.solver.core.api.score.stream.Constraint
+import ai.timefold.solver.core.api.score.stream.ConstraintFactory
+import ai.timefold.solver.core.api.score.stream.ConstraintProvider
+
+import org.acme.vehiclerouting.domain.Visit
+import org.acme.vehiclerouting.domain.Vehicle
+import org.acme.vehiclerouting.solver.justifications.MinimizeTravelTimeJustification
+import org.acme.vehiclerouting.solver.justifications.ServiceFinishedAfterMaxEndTimeJustification
+import org.acme.vehiclerouting.solver.justifications.VehicleCapacityJustification
+
+class VehicleRoutingConstraintProvider : ConstraintProvider {
+    override fun defineConstraints(factory: ConstraintFactory): Array<Constraint> {
+        return arrayOf(
+            vehicleCapacity(factory),
+            serviceFinishedAfterMaxEndTime(factory),
+            minimizeTravelTime(factory)
+        )
+    }
+
+    protected fun vehicleCapacity(factory: ConstraintFactory): Constraint {
+        return factory.forEach(Vehicle::class.java)
+            .filter({ vehicle: Vehicle -> vehicle.totalDemand > vehicle.capacity })
+            .penalizeLong(
+                HardSoftLongScore.ONE_HARD
+            ) { vehicle: Vehicle -> vehicle.totalDemand - vehicle.capacity }
+            .justifyWith({ vehicle: Vehicle, score: HardSoftLongScore? ->
+                VehicleCapacityJustification(
+                    vehicle.id, vehicle.totalDemand.toInt(),
+                    vehicle.capacity
+                )
+            })
+            .asConstraint(VEHICLE_CAPACITY)
+    }
+
+    protected fun serviceFinishedAfterMaxEndTime(factory: ConstraintFactory): Constraint {
+        return factory.forEach(Visit::class.java)
+            .filter({ obj: Visit -> obj.isServiceFinishedAfterMaxEndTime })
+            .penalizeLong(HardSoftLongScore.ONE_HARD,
+                { obj: Visit -> obj.serviceFinishedDelayInMinutes })
+            .justifyWith({ visit: Visit, score: HardSoftLongScore? ->
+                ServiceFinishedAfterMaxEndTimeJustification(
+                    visit.id,
+                    visit.serviceFinishedDelayInMinutes
+                )
+            })
+            .asConstraint(SERVICE_FINISHED_AFTER_MAX_END_TIME)
+    }
+
+    protected fun minimizeTravelTime(factory: ConstraintFactory): Constraint {
+        return factory.forEach(Vehicle::class.java)
+            .penalizeLong(HardSoftLongScore.ONE_SOFT,
+                { obj: Vehicle -> obj.totalDrivingTimeSeconds })
+            .justifyWith({ vehicle: Vehicle, score: HardSoftLongScore? ->
+                MinimizeTravelTimeJustification(
+                    vehicle.id,
+                    vehicle.totalDrivingTimeSeconds
+                )
+            })
+            .asConstraint(MINIMIZE_TRAVEL_TIME)
+    }
+
+    companion object {
+        const val VEHICLE_CAPACITY: String = "vehicleCapacity"
+        const val SERVICE_FINISHED_AFTER_MAX_END_TIME: String = "serviceFinishedAfterMaxEndTime"
+        const val MINIMIZE_TRAVEL_TIME: String = "minimizeTravelTime"
+    }
+}
+----
+--
+====
+
+The `ConstraintProvider` scales much better than the `EasyScoreCalculator`: typically __O__(n) instead of __O__(n²).