public AlgorithmExecutor(
List<City> cities,
City depot,
int numberOfDrones,
int numberOfGenerations,
int populationSize,
double crossoverProbability,
double mutationProbability,
bool fitnessConsidersPartitions,
bool isCalibration)
{
CITIES = cities;
DEPOT = depot;
NUMBER_OF_CITIES = cities.Count;
NUMBER_OF_DRONES = numberOfDrones;
NUMBER_OF_GENERATIONS = numberOfGenerations;
POPULATION_SIZE = populationSize;
CROSSOVER_PROBABILITY = crossoverProbability;
MUTATION_PROBABILITY = mutationProbability;
FITNESS_CONSIDERS_PARTITIONS = fitnessConsidersPartitions;
IS_CALIBRATION = isCalibration;
}
public PartitionAlgorithm(List<City> TSPSequence, City depot, int numberOfDrones)
{
cities = TSPSequence;
this.depot = depot;
this.numberOfDrones = numberOfDrones;
}
// Runs the GA with the given parameters.
private static void runGAWithParams(
string fileName,
int numberOfDrones,
bool fitnessConsidersPartitions,
int population,
double crossover,
double mutation,
int numberOfGenerations)
{
NUMBER_OF_DRONES = numberOfDrones;
var lines = File.ReadAllLines(fileName + ".txt");
foreach (var line in lines)
{
string[] coords = line.Split(' ');
if (coords[0].Equals("1"))
{
DEPOT = new City("Depot", double.Parse(coords[1]), double.Parse(coords[2]));
}
else
{
CITIES.Add(new City("City " + coords[0], double.Parse(coords[1]), double.Parse(coords[2])));
}
}
AlgorithmExecutor executor = new AlgorithmExecutor(
CITIES, DEPOT, NUMBER_OF_DRONES, numberOfGenerations, population, crossover, mutation,
fitnessConsidersPartitions, false /* isCalibration */);
executor.RunGAInstance();
// Write the results from the simulation with the given number of drones
// to the specified file.
Utils.writeResultsToFile(fileName, numberOfDrones);
CITIES.Clear();
}
private static void Main(string[] args)
{
CITIES = new List<City>();
Console.WriteLine("To run the calibration mode (100 random instances), press 'C' or 'c' and then ENTER.");
Console.WriteLine("The results will then be stored as 'output_strat1.txt' and 'output_strat2.txt'.");
Console.WriteLine("Otherwise, press just ENTER and the application will run the 3 sample instances.");
// Read user input.
string input = Console.ReadLine();
if (input != "c" && input != "C")
{
List<string> inputFiles = new List<string>();
// Add the input files.
inputFiles.Add("eil51");
inputFiles.Add("eil76");
inputFiles.Add("rat99");
for (int i = 0; i < inputFiles.Count; i++)
{
string inputFile = inputFiles[i];
// Run GA with selected parameters three times: for 2, 3 and 5 travelers.
// Running for the case that fitness calculates the cost of TSP.
runGAWithParams(inputFile, 2, false, 200, 0.6, 0.1, NUMBER_OF_GENERATIONS_STRAT_1);
runGAWithParams(inputFile, 3, false, 200, 0.6, 0.1, NUMBER_OF_GENERATIONS_STRAT_1);
runGAWithParams(inputFile, 5, false, 200, 0.6, 0.1, NUMBER_OF_GENERATIONS_STRAT_1);
// Running for the case that fitness calculates the cost of mTSP
// using the greedy algorithm.
runGAWithParams(inputFile, 2, true, 200, 1, 0, NUMBER_OF_GENERATIONS_STRAT_2);
runGAWithParams(inputFile, 3, true, 200, 1, 0, NUMBER_OF_GENERATIONS_STRAT_2);
runGAWithParams(inputFile, 5, true, 200, 1, 0, NUMBER_OF_GENERATIONS_STRAT_2);
}
}
else
{
DEPOT = new City("Depot", 0.0, 0.0);
CITIES = Utils.CreateCities().ToList();
// 100 test cases runs for both approaches.
calibrateGA(false /* fitnessConsidersPartitions */, NUMBER_OF_GENERATIONS_CALIBRATION_STRAT_1);
calibrateGA(true /* fitnessConsidersPartitions */, NUMBER_OF_GENERATIONS_CALIBRATION_STRAT_2);
}
Console.WriteLine("SIMULATION ENDED.");
Console.ReadLine();
}
public GreedyAlgorithm(List<City> TSPSequence, City depot, int numberOfDrones)
: base(TSPSequence, depot, numberOfDrones)
{
}
