最新的几个VRP问题求解的开源工具

import VRPSolverEasy as vrpseimport math
def compute_euclidean_distance(x_i, x_j, y_i, y_j):  """compute the euclidean distance between 2 points from graph"""     return round(math.sqrt((x_i - x_j)**2 +                            (y_i - y_j)**2), 3)
# Datacost_per_distance = 10begin_time = 0end_time = 5000nb_point = 7
# Map with names and coordinatescoordinates = {"Wisconsin, USA": (44.50, -89.50),  # depot               "West Virginia, USA": (39.000000, -80.500000),               "Vermont, USA": (44.000000, -72.699997),               "Texas, the USA": (31.000000, -100.000000),               "South Dakota, the US": (44.500000, -100.000000),               "Rhode Island, the US": (41.742325, -71.742332),               "Oregon, the US": (44.000000, -120.500000)               }
# Demands of pointsdemands = [0, 500, 300, 600, 658, 741, 436]
# Initialisationmodel = vrpse.Model()
# Add vehicle typemodel.add_vehicle_type(    id=1,    start_point_id=0,    end_point_id=0,    name="VEH1",    capacity=1100,    max_number=6,    var_cost_dist=cost_per_distance,    tw_end=5000)
# Add depotmodel.add_depot(id=0, name="D1", tw_begin=0, tw_end=5000)
coordinates_keys = list(coordinates.keys())# Add customersfor i in range(1, nb_point):    model.add_customer(        id=i,        name=coordinates_keys[i],        demand=demands[i],        tw_begin=begin_time,        tw_end=end_time)
# Add linkscoordinates_values = list(coordinates.values())for i in range(0, 7):    for j in range(i + 1, 7):        dist = compute_euclidean_distance(coordinates_values[i][0],                                          coordinates_values[j][0],                                          coordinates_values[i][1],                                          coordinates_values[j][1])        model.add_link(            start_point_id=i,            end_point_id=j,            distance=dist,            time=dist)
# solve modelmodel.solve()model.export()
if model.solution.is_defined():    print(model.solution)

package SearchMethod;
import java.lang.reflect.InvocationTargetException;import java.text.DecimalFormat;import java.util.HashMap;import java.util.Random;import Auxiliary.Distance;import Data.Instance;import DiversityControl.DistAdjustment;import DiversityControl.OmegaAdjustment;import DiversityControl.AcceptanceCriterion;import DiversityControl.IdealDist;import Improvement.LocalSearch;import Improvement.IntraLocalSearch;import Improvement.FeasibilityPhase;import Perturbation.InsertionHeuristic;import Perturbation.Perturbation;import Solution.Solution;public class AILSII {  //----------Problema------------  Solution solution,referenceSolution,bestSolution;    Instance instance;  Distance pairwiseDistance;  double bestF=Double.MAX_VALUE;  double executionMaximumLimit;  double optimal;    //----------caculoLimiar------------  int numIterUpdate;  //----------Metricas------------  int iterator,iteratorMF;  long first,ini;  double timeAF,totalTime,time;    Random rand=new Random();    HashMap<String,OmegaAdjustment>omegaSetup=new HashMap<String,OmegaAdjustment>();  double distanceLS;    Perturbation[] pertubOperators;  Perturbation selectedPerturbation;    FeasibilityPhase feasibilityOperator;  ConstructSolution constructSolution;    LocalSearch localSearch;  InsertionHeuristic insertionHeuristic;  IntraLocalSearch intraLocalSearch;  AcceptanceCriterion acceptanceCriterion;//  ----------Mare------------  DistAdjustment distAdjustment;//  ---------Print----------  boolean print=true;  IdealDist idealDist;    double epsilon;  DecimalFormat deci=new DecimalFormat("0.0000");  StoppingCriterionType stoppingCriterionType;    public AILSII(Instance instance,InputParameters reader){     this.instance=instance;    Config config=reader.getConfig();    this.optimal=reader.getBest();    this.executionMaximumLimit=reader.getTimeLimit();        this.epsilon=config.getEpsilon();    this.stoppingCriterionType=config.getStoppingCriterionType();    this.idealDist=new IdealDist();    this.solution =new Solution(instance,config);    this.referenceSolution =new Solution(instance,config);    this.bestSolution =new Solution(instance,config);    this.numIterUpdate=config.getGamma();        this.pairwiseDistance=new Distance();        this.pertubOperators=new Perturbation[config.getPerturbation().length];        this.distAdjustment=new DistAdjustment( idealDist, config, executionMaximumLimit);        this.intraLocalSearch=new IntraLocalSearch(instance,config);        this.localSearch=new LocalSearch(instance,config,intraLocalSearch);        this.feasibilityOperator=new FeasibilityPhase(instance,config,intraLocalSearch);        this.constructSolution=new ConstructSolution(instance,config);        OmegaAdjustment newOmegaAdjustment;    for (int i = 0; i < config.getPerturbation().length; i++)     {      newOmegaAdjustment=new OmegaAdjustment(config.getPerturbation()[i], config,instance.getSize(),idealDist);      omegaSetup.put(config.getPerturbation()[i]+"", newOmegaAdjustment);    }        this.acceptanceCriterion=new AcceptanceCriterion(instance,config,executionMaximumLimit);    try     {      for (int i = 0; i < pertubOperators.length; i++)       {        this.pertubOperators[i]=(Perturbation) Class.forName("Perturbation."+config.getPerturbation()[i]).        getConstructor(Instance.class,Config.class,HashMap.class,IntraLocalSearch.class).        newInstance(instance,config,omegaSetup,intraLocalSearch);      }          } catch (InstantiationException | IllegalAccessException | IllegalArgumentException        | InvocationTargetException | NoSuchMethodException | SecurityException        | ClassNotFoundException e) {      e.printStackTrace();    }      }  public void search(){    iterator=0;    first=System.currentTimeMillis();    referenceSolution.numRoutes=instance.getMinNumberRoutes();    constructSolution.construct(referenceSolution);        feasibilityOperator.makeFeasible(referenceSolution);    localSearch.localSearch(referenceSolution,true);    bestSolution.clone(referenceSolution);    while(!stoppingCriterion())    {      iterator++;      solution.clone(referenceSolution);            selectedPerturbation=pertubOperators[rand.nextInt(pertubOperators.length)];      selectedPerturbation.applyPerturbation(solution);      feasibilityOperator.makeFeasible(solution);      localSearch.localSearch(solution,true);      distanceLS=pairwiseDistance.pairwiseSolutionDistance(solution,referenceSolution);            evaluateSolution();      distAdjustment.distAdjustment();            selectedPerturbation.getChosenOmega().setDistance(distanceLS);//update            if(acceptanceCriterion.acceptSolution(solution))        referenceSolution.clone(solution);    }        totalTime=(double)(System.currentTimeMillis()-first)/1000;  }    public void evaluateSolution(){    if((solution.f-bestF)<-epsilon)    {          bestF=solution.f;            bestSolution.clone(solution);      iteratorMF=iterator;      timeAF=(double)(System.currentTimeMillis()-first)/1000;              if(print)      {        System.out.println("solution quality: "+bestF        +" gap: "+deci.format(getGap())+"%"        +" K: "+solution.numRoutes        +" iteration: "+iterator        +" eta: "+deci.format(acceptanceCriterion.getEta())        +" omega: "+deci.format(selectedPerturbation.omega)        +" time: "+timeAF        );      }    }  }    private boolean stoppingCriterion(){    switch(stoppingCriterionType)    {      case Iteration:   if(bestF<=optimal||executionMaximumLimit<=iterator)                  return true;                break;                    case Time:   if(bestF<=optimal||executionMaximumLimit<(System.currentTimeMillis()-first)/1000)              return true;            break;    }    return false;  }    public static void main(String[] args) {    InputParameters reader=new InputParameters();    reader.readingInput(args);        Instance instance=new Instance(reader);        AILSII ailsII=new AILSII(instance,reader);        ailsII.search();  }    public Solution getBestSolution() {    return bestSolution;  }  public double getBestF() {    return bestF;  }  public double getGap(){    return 100*((bestF-optimal)/optimal);  }    public boolean isPrint() {    return print;  }  public void setPrint(boolean print) {    this.print = print;  }  public Solution getSolution() {    return solution;  }  public int getIterator() {    return iterator;  }  public String printOmegas(){    String str="";    for (int i = 0; i < pertubOperators.length; i++)     {      str+="\n"+omegaSetup.get(this.pertubOperators[i].perturbationType+""+referenceSolution.numRoutes);    }    return str;  }    public Perturbation[] getPertubOperators() {    return pertubOperators;  }    public double getTotalTime() {    return totalTime;  }    public double getTimePerIteration() {    return totalTime/iterator;  }  public double getTimeAF() {    return timeAF;  }  public int getIteratorMF() {    return iteratorMF;  }    public double getConvergenceIteration(){    return (double)iteratorMF/iterator;  }    public double convergenceTime(){    return (double)timeAF/totalTime;  }  }