312 lines
12 KiB
Java
312 lines
12 KiB
Java
//
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// Copyright 2012 Google
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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import com.google.ortools.constraintsolver.Assignment;
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import com.google.ortools.constraintsolver.FirstSolutionStrategy;
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import com.google.ortools.constraintsolver.IntVar;
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import com.google.ortools.constraintsolver.RoutingDimension;
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import com.google.ortools.constraintsolver.RoutingIndexManager;
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import com.google.ortools.constraintsolver.RoutingModel;
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import com.google.ortools.constraintsolver.RoutingSearchParameters;
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import com.google.ortools.constraintsolver.main;
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import java.util.ArrayList;
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import java.util.List;
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import java.util.Random;
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import java.util.function.LongBinaryOperator;
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import java.util.function.LongUnaryOperator;
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import java.util.logging.Logger;
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// A pair class
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class Pair<K, V> {
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final K first;
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final V second;
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public static <K, V> Pair<K, V> of(K element0, V element1) {
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return new Pair<K, V>(element0, element1);
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}
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public Pair(K element0, V element1) {
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this.first = element0;
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this.second = element1;
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}
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}
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/**
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* Sample showing how to model and solve a capacitated vehicle routing problem with time windows
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* using the swig-wrapped version of the vehicle routing library in src/constraint_solver.
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*/
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public class CapacitatedVehicleRoutingProblemWithTimeWindows {
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static {
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System.loadLibrary("jniortools");
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}
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private static Logger logger =
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Logger.getLogger(CapacitatedVehicleRoutingProblemWithTimeWindows.class.getName());
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// Locations representing either an order location or a vehicle route
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// start/end.
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private List<Pair<Integer, Integer>> locations = new ArrayList();
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// Quantity to be picked up for each order.
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private List<Integer> orderDemands = new ArrayList();
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// Time window in which each order must be performed.
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private List<Pair<Integer, Integer>> orderTimeWindows = new ArrayList();
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// Penalty cost "paid" for dropping an order.
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private List<Integer> orderPenalties = new ArrayList();
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// Capacity of the vehicles.
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private int vehicleCapacity = 0;
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// Latest time at which each vehicle must end its tour.
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private List<Integer> vehicleEndTime = new ArrayList();
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// Cost per unit of distance of each vehicle.
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private List<Integer> vehicleCostCoefficients = new ArrayList();
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// Vehicle start and end indices. They have to be implemented as int[] due
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// to the available SWIG-ed interface.
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private int vehicleStarts[];
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private int vehicleEnds[];
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// Random number generator to produce data.
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private final Random randomGenerator = new Random(0xBEEF);
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/**
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* Creates a Manhattan Distance evaluator with 'costCoefficient'.
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*
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* @param manager Node Index Manager.
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* @param costCoefficient The coefficient to apply to the evaluator.
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*/
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private LongBinaryOperator buildManhattanCallback(RoutingIndexManager manager, int costCoefficient) {
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return new LongBinaryOperator() {
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public long applyAsLong(long firstIndex, long secondIndex) {
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try {
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int firstNode = manager.indexToNode(firstIndex);
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int secondNode = manager.indexToNode(secondIndex);
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Pair<Integer, Integer> firstLocation = locations.get(firstNode);
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Pair<Integer, Integer> secondLocation = locations.get(secondNode);
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return (long) costCoefficient
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* (Math.abs(firstLocation.first - secondLocation.first)
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+ Math.abs(firstLocation.second - secondLocation.second));
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} catch (Throwable throwed) {
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logger.warning(throwed.getMessage());
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return 0;
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}
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}
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};
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}
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/**
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* Creates order data. Location of the order is random, as well as its demand (quantity), time
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* window and penalty.
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*
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* @param numberOfOrders number of orders to build.
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* @param xMax maximum x coordinate in which orders are located.
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* @param yMax maximum y coordinate in which orders are located.
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* @param demandMax maximum quantity of a demand.
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* @param timeWindowMax maximum starting time of the order time window.
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* @param timeWindowWidth duration of the order time window.
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* @param penaltyMin minimum pernalty cost if order is dropped.
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* @param penaltyMax maximum pernalty cost if order is dropped.
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*/
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private void buildOrders(
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int numberOfOrders,
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int xMax,
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int yMax,
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int demandMax,
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int timeWindowMax,
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int timeWindowWidth,
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int penaltyMin,
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int penaltyMax) {
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logger.info("Building orders.");
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for (int order = 0; order < numberOfOrders; ++order) {
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locations.add(Pair.of(randomGenerator.nextInt(xMax + 1), randomGenerator.nextInt(yMax + 1)));
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orderDemands.add(randomGenerator.nextInt(demandMax + 1));
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int timeWindowStart = randomGenerator.nextInt(timeWindowMax + 1);
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orderTimeWindows.add(Pair.of(timeWindowStart, timeWindowStart + timeWindowWidth));
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orderPenalties.add(randomGenerator.nextInt(penaltyMax - penaltyMin + 1) + penaltyMin);
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}
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}
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/**
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* Creates fleet data. Vehicle starting and ending locations are random, as well as vehicle costs
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* per distance unit.
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*
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* @param numberOfVehicles
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* @param xMax maximum x coordinate in which orders are located.
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* @param yMax maximum y coordinate in which orders are located.
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* @param endTime latest end time of a tour of a vehicle.
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* @param capacity capacity of a vehicle.
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* @param costCoefficientMax maximum cost per distance unit of a vehicle (mimimum is 1),
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*/
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private void buildFleet(
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int numberOfVehicles, int xMax, int yMax, int endTime, int capacity, int costCoefficientMax) {
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logger.info("Building fleet.");
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vehicleCapacity = capacity;
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vehicleStarts = new int[numberOfVehicles];
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vehicleEnds = new int[numberOfVehicles];
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for (int vehicle = 0; vehicle < numberOfVehicles; ++vehicle) {
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vehicleStarts[vehicle] = locations.size();
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locations.add(Pair.of(randomGenerator.nextInt(xMax + 1), randomGenerator.nextInt(yMax + 1)));
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vehicleEnds[vehicle] = locations.size();
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locations.add(Pair.of(randomGenerator.nextInt(xMax + 1), randomGenerator.nextInt(yMax + 1)));
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vehicleEndTime.add(endTime);
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vehicleCostCoefficients.add(randomGenerator.nextInt(costCoefficientMax) + 1);
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}
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}
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/** Solves the current routing problem. */
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private void solve(final int numberOfOrders, final int numberOfVehicles) {
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logger.info(
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"Creating model with " + numberOfOrders + " orders and " + numberOfVehicles + " vehicles.");
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// Finalizing model
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final int numberOfLocations = locations.size();
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RoutingIndexManager manager =
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new RoutingIndexManager(numberOfLocations, numberOfVehicles, vehicleStarts, vehicleEnds);
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RoutingModel model = new RoutingModel(manager);
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// Setting up dimensions
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final int bigNumber = 100000;
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final LongBinaryOperator callback = buildManhattanCallback(manager, 1);
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final String timeStr = "time";
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model.addDimension(
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model.registerTransitCallback(callback), bigNumber, bigNumber, false, timeStr);
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RoutingDimension timeDimension = model.getMutableDimension(timeStr);
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LongUnaryOperator demandCallback =
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new LongUnaryOperator() {
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public long applyAsLong(long index) {
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try {
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int node = manager.indexToNode(index);
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if (node < numberOfOrders) {
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return orderDemands.get(node);
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}
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return 0;
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} catch (Throwable throwed) {
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logger.warning(throwed.getMessage());
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return 0;
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}
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}
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};
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final String capacityStr = "capacity";
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model.addDimension(
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model.registerUnaryTransitCallback(demandCallback), 0, vehicleCapacity, true, capacityStr);
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RoutingDimension capacityDimension = model.getMutableDimension(capacityStr);
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// Setting up vehicles
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LongBinaryOperator[] callbacks = new LongBinaryOperator[numberOfVehicles];
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for (int vehicle = 0; vehicle < numberOfVehicles; ++vehicle) {
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final int costCoefficient = vehicleCostCoefficients.get(vehicle);
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callbacks[vehicle] = buildManhattanCallback(manager, costCoefficient);
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final int vehicleCost = model.registerTransitCallback(callbacks[vehicle]);
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model.setArcCostEvaluatorOfVehicle(vehicleCost, vehicle);
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timeDimension.cumulVar(model.end(vehicle)).setMax(vehicleEndTime.get(vehicle));
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}
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// Setting up orders
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for (int order = 0; order < numberOfOrders; ++order) {
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timeDimension
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.cumulVar(order)
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.setRange(orderTimeWindows.get(order).first, orderTimeWindows.get(order).second);
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long[] orderIndices = {manager.nodeToIndex(order)};
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model.addDisjunction(orderIndices, orderPenalties.get(order));
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}
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// Solving
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RoutingSearchParameters parameters =
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main.defaultRoutingSearchParameters()
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.toBuilder()
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.setFirstSolutionStrategy(FirstSolutionStrategy.Value.ALL_UNPERFORMED)
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.build();
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logger.info("Search");
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Assignment solution = model.solveWithParameters(parameters);
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if (solution != null) {
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String output = "Total cost: " + solution.objectiveValue() + "\n";
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// Dropped orders
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String dropped = "";
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for (int order = 0; order < numberOfOrders; ++order) {
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if (solution.value(model.nextVar(order)) == order) {
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dropped += " " + order;
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}
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}
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if (dropped.length() > 0) {
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output += "Dropped orders:" + dropped + "\n";
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}
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// Routes
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for (int vehicle = 0; vehicle < numberOfVehicles; ++vehicle) {
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String route = "Vehicle " + vehicle + ": ";
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long order = model.start(vehicle);
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// Empty route has a minimum of two nodes: Start => End
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if (model.isEnd(solution.value(model.nextVar(order)))) {
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route += "Empty";
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} else {
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for (; !model.isEnd(order); order = solution.value(model.nextVar(order))) {
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IntVar load = capacityDimension.cumulVar(order);
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IntVar time = timeDimension.cumulVar(order);
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route +=
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order
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+ " Load("
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+ solution.value(load)
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+ ") "
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+ "Time("
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+ solution.min(time)
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+ ", "
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+ solution.max(time)
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+ ") -> ";
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}
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IntVar load = capacityDimension.cumulVar(order);
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IntVar time = timeDimension.cumulVar(order);
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route +=
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order
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+ " Load("
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+ solution.value(load)
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+ ") "
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+ "Time("
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+ solution.min(time)
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+ ", "
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+ solution.max(time)
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+ ")";
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}
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output += route + "\n";
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}
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logger.info(output);
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}
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}
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public static void main(String[] args) throws Exception {
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CapacitatedVehicleRoutingProblemWithTimeWindows problem =
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new CapacitatedVehicleRoutingProblemWithTimeWindows();
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final int xMax = 20;
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final int yMax = 20;
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final int demandMax = 3;
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final int timeWindowMax = 24 * 60;
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final int timeWindowWidth = 4 * 60;
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final int penaltyMin = 50;
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final int penaltyMax = 100;
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final int endTime = 24 * 60;
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final int costCoefficientMax = 3;
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final int orders = 100;
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final int vehicles = 20;
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final int capacity = 50;
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problem.buildOrders(
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orders, xMax, yMax, demandMax, timeWindowMax, timeWindowWidth, penaltyMin, penaltyMax);
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problem.buildFleet(vehicles, xMax, yMax, endTime, capacity, costCoefficientMax);
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problem.solve(orders, vehicles);
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}
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}
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