/******************************************************************************* * Copyright (c) 2013 Stefan Schroeder. * * This library is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 3.0 of the License, or (at your option) any later version. * * This library is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this library. If not, see . * * Contributors: * Stefan Schroeder - initial API and implementation ******************************************************************************/ package jsprit.examples; import java.util.Collection; import jsprit.analysis.toolbox.SolutionPrinter; import jsprit.core.algorithm.InsertionInitialSolutionFactory; import jsprit.core.algorithm.RemoveEmptyVehicles; import jsprit.core.algorithm.SearchStrategy; import jsprit.core.algorithm.SearchStrategyManager; import jsprit.core.algorithm.VariablePlusFixedSolutionCostCalculatorFactory; import jsprit.core.algorithm.VehicleRoutingAlgorithm; import jsprit.core.algorithm.acceptor.GreedyAcceptance; import jsprit.core.algorithm.module.RuinAndRecreateModule; import jsprit.core.algorithm.recreate.BestInsertionBuilder; import jsprit.core.algorithm.recreate.InsertionStrategy; import jsprit.core.algorithm.ruin.RadialRuinStrategyFactory; import jsprit.core.algorithm.ruin.RandomRuinStrategyFactory; import jsprit.core.algorithm.ruin.RuinStrategy; import jsprit.core.algorithm.ruin.distance.AvgServiceAndShipmentDistance; import jsprit.core.algorithm.selector.SelectBest; import jsprit.core.algorithm.state.StateManager; import jsprit.core.algorithm.state.UpdateVariableCosts; import jsprit.core.algorithm.termination.IterationWithoutImprovementTermination; import jsprit.core.problem.VehicleRoutingProblem; import jsprit.core.problem.constraint.ConstraintManager; import jsprit.core.problem.solution.SolutionCostCalculator; import jsprit.core.problem.solution.VehicleRoutingProblemSolution; import jsprit.core.problem.vehicle.InfiniteFleetManagerFactory; import jsprit.core.problem.vehicle.VehicleFleetManager; import jsprit.core.util.Solutions; import jsprit.instance.reader.SolomonReader; import jsprit.util.Examples; public class BuildAlgorithmFromScratch { /** * @param args */ public static void main(String[] args) { /* * some preparation - create output folder */ Examples.createOutputFolder(); /* * Build the problem. * * But define a problem-builder first. */ VehicleRoutingProblem.Builder vrpBuilder = VehicleRoutingProblem.Builder.newInstance(); /* * A solomonReader reads solomon-instance files, and stores the required information in the builder. */ new SolomonReader(vrpBuilder).read("input/C101_solomon.txt"); /* * Finally, the problem can be built. By default, transportCosts are crowFlyDistances (as usually used for vrp-instances). */ VehicleRoutingProblem vrp = vrpBuilder.build(); /* * Build algorithm */ VehicleRoutingAlgorithm vra = buildAlgorithmFromScratch(vrp); /* * search solution */ Collection solutions = vra.searchSolutions(); /* * print result */ SolutionPrinter.print(Solutions.bestOf(solutions)); } private static VehicleRoutingAlgorithm buildAlgorithmFromScratch(VehicleRoutingProblem vrp) { /* * manages route and activity states. */ StateManager stateManager = new StateManager(vrp); /* * tells stateManager to update load states */ stateManager.updateLoadStates(); /* * tells stateManager to update time-window states */ stateManager.updateTimeWindowStates(); /* * stateManager.addStateUpdater(updater); * lets you register your own stateUpdater */ /* * updates variable costs once a vehicleRoute has changed (by removing or adding a customer) */ stateManager.addStateUpdater(new UpdateVariableCosts(vrp.getActivityCosts(), vrp.getTransportCosts(), stateManager)); /* * constructs a constraintManager that manages the various hardConstraints (and soon also softConstraints) */ ConstraintManager constraintManager = new ConstraintManager(vrp,stateManager); /* * tells constraintManager to add timeWindowConstraints */ constraintManager.addTimeWindowConstraint(); /* * tells constraintManager to add loadConstraints */ constraintManager.addLoadConstraint(); /* * add an arbitrary number of hardConstraints by * constraintManager.addConstraint(...) */ /* * define a fleetManager, here infinite vehicles can be used */ VehicleFleetManager fleetManager = new InfiniteFleetManagerFactory(vrp.getVehicles()).createFleetManager(); /* * define ruin-and-recreate strategies * */ /* * first, define an insertion-strategy, i.e. bestInsertion */ BestInsertionBuilder iBuilder = new BestInsertionBuilder(vrp, fleetManager, stateManager, constraintManager); /* * no need to set further options */ InsertionStrategy iStrategy = iBuilder.build(); /* * second, define random-ruin that ruins 50-percent of the selected solution */ RuinStrategy randomRuin = new RandomRuinStrategyFactory(0.5).createStrategy(vrp); /* * third, define radial-ruin that ruins 30-percent of the selected solution * the second para defines the distance between two jobs. */ RuinStrategy radialRuin = new RadialRuinStrategyFactory(0.3, new AvgServiceAndShipmentDistance(vrp.getTransportCosts())).createStrategy(vrp); /* * now define a strategy */ /* * but before define how a generated solution is evaluated * here: the VariablePlusFixed.... comes out of the box and it does what its name suggests */ SolutionCostCalculator solutionCostCalculator = new VariablePlusFixedSolutionCostCalculatorFactory(stateManager).createCalculator(); SearchStrategy firstStrategy = new SearchStrategy(new SelectBest(), new GreedyAcceptance(1), solutionCostCalculator); firstStrategy.addModule(new RuinAndRecreateModule("randomRuinAndBestInsertion", iStrategy, randomRuin)); SearchStrategy secondStrategy = new SearchStrategy(new SelectBest(), new GreedyAcceptance(1), solutionCostCalculator); secondStrategy.addModule(new RuinAndRecreateModule("radialRuinAndBestInsertion", iStrategy, radialRuin)); /* * put both strategies together, each with the prob of 0.5 to be selected */ SearchStrategyManager searchStrategyManager = new SearchStrategyManager(); searchStrategyManager.addStrategy(firstStrategy, 0.5); searchStrategyManager.addStrategy(secondStrategy, 0.5); /* * construct the algorithm */ VehicleRoutingAlgorithm vra = new VehicleRoutingAlgorithm(vrp, searchStrategyManager); //do not forgett to add the stateManager listening to the algorithm-stages vra.addListener(stateManager); //remove empty vehicles after insertion has finished vra.addListener(new RemoveEmptyVehicles(fleetManager)); /* * Do not forget to add an initial solution by vra.addInitialSolution(solution); * or */ vra.addInitialSolution(new InsertionInitialSolutionFactory(iStrategy, solutionCostCalculator).createSolution(vrp)); /* * define the nIterations (by default nIteration=100) */ vra.setNuOfIterations(1000); /* * optionally define a premature termination criterion (by default: not criterion is set) */ vra.setPrematureAlgorithmTermination(new IterationWithoutImprovementTermination(100)); return vra; } }