public void Start(string inputFile, string outputFile, int timeLimit) { TSPInstance instance = new TSPInstance(inputFile); DiscreteSS ss = new DiscreteSS2OptBest4TSP(instance, poolSize, refSetSize, explorationFactor); ss.Run(timeLimit - timePenalty); TSPSolution solution = new TSPSolution(instance, ss.BestSolution); solution.Write(outputFile); }
public void Start(string fileInput, string fileOutput, int timeLimit) { TSPInstance instance = new TSPInstance(fileInput); int[] assignment = TSPUtils.GreedySolution(instance); TSPUtils.LocalSearch2OptFirst(instance, assignment); TSPSolution solution = new TSPSolution(instance, assignment); solution.Write(fileOutput); }
public void Start(string inputFile, string outputFile, int timeLimit) { TSPInstance instance = new TSPInstance(inputFile); int levelLength = (int) Math.Ceiling(levelLengthFactor * (instance.NumberCities * (instance.NumberCities - 1))); DiscreteHMSAwGRASP2OptBest4TSP hm = new DiscreteHMSAwGRASP2OptBest4TSP(instance, rclTreshold, graspIterations, initialSolutions, levelLength, tempReduction); hm.Run(timeLimit - timePenalty); TSPSolution solution = new TSPSolution(instance, hm.BestSolution); solution.Write(outputFile); }
public void Start(string fileInput, string fileOutput, int timeLimit) { TSPInstance instance = new TSPInstance(fileInput); int levelLength = (int) Math.Ceiling(levelLengthFactor * (instance.NumberCities * (instance.NumberCities - 1))); DiscreteSA sa = new DiscreteSA4TSP(instance, initialSolutions, levelLength, tempReduction); sa.Run(timeLimit - timePenalty); TSPSolution solution = new TSPSolution(instance, sa.BestSolution); solution.Write(fileOutput); }
public void Start(string inputFile, string outputFile, int timeLimit) { TSPInstance instance = new TSPInstance(inputFile); MaxMinAntSystem aco = new MaxMinAntSystem2OptBest4TSP(instance, numberAnts, rho, alpha, beta, maxReinit, candidateLength, candidateWeight); // Solving the problem and writing the best solution found. aco.Run(timeLimit - timePenalty); TSPSolution solution = new TSPSolution(instance, aco.BestSolution); solution.Write(outputFile); }
public void Start(string inputFile, string outputFile, int timeLimit) { TSPInstance instance = new TSPInstance(inputFile); int neighborChecks = (int) Math.Ceiling(neighborChecksFactor * (instance.NumberCities * (instance.NumberCities - 1))); int tabuListLength = (int) Math.Ceiling(tabuListFactor * instance.NumberCities); DiscreteTS ts = new DiscreteTS4TSP(instance, rclTreshold, tabuListLength, neighborChecks); ts.Run(timeLimit - timePenalty); TSPSolution solution = new TSPSolution(instance, ts.BestSolution); solution.Write(outputFile); }
public void Start(string inputFile, string outputFile, int timeLimit) { TSPInstance instance = new TSPInstance(inputFile); DiscreteSS ss = new DiscreteSS4TSP(instance, poolSize, refSetSize, explorationFactor); ss.Run(timeLimit - timePenalty); TSPSolution solution = new TSPSolution(instance, ss.BestSolution); solution.Write(outputFile); }
public void Start(string inputFile, string outputFile, int timeLimit) { TSPInstance instance = new TSPInstance(inputFile); int levelLength = (int)Math.Ceiling(levelLengthFactor * (instance.NumberCities * (instance.NumberCities - 1))); DiscreteHMSAwGRASP2OptFirst4TSP hm = new DiscreteHMSAwGRASP2OptFirst4TSP(instance, rclTreshold, graspIterations, initialSolutions, levelLength, tempReduction); hm.Run(timeLimit - timePenalty); TSPSolution solution = new TSPSolution(instance, hm.BestSolution); solution.Write(outputFile); }
public void Start(string fileInput, string fileOutput, int timeLimit) { TSPInstance instance = new TSPInstance(fileInput); int levelLength = (int)Math.Ceiling(levelLengthFactor * (instance.NumberCities * (instance.NumberCities - 1))); DiscreteSA sa = new DiscreteSA4TSP(instance, initialSolutions, levelLength, tempReduction); sa.Run(timeLimit - timePenalty); TSPSolution solution = new TSPSolution(instance, sa.BestSolution); solution.Write(fileOutput); }
public void Start(string fileInput, string fileOutput, int timeLimit) { TSPInstance instance = new TSPInstance(fileInput); // Setting the parameters of the GRASP for this instance of the problem. DiscreteGRASP grasp = new DiscreteGRASP2OptBest4TSP(instance, rclThreshold); // Solving the problem and writing the best solution found. grasp.Run(timeLimit - (int)timePenalty, RunType.TimeLimit); TSPSolution solution = new TSPSolution(instance, grasp.BestSolution); solution.Write(fileOutput); }
public void Start(string inputFile, string outputFile, int timeLimit) { TSPInstance instance = new TSPInstance(inputFile); int neighborChecks = (int)Math.Ceiling(neighborChecksFactor * (instance.NumberCities * (instance.NumberCities - 1))); int tabuListLength = (int)Math.Ceiling(tabuListFactor * instance.NumberCities); DiscreteTS ts = new DiscreteTS4TSP(instance, rclTreshold, tabuListLength, neighborChecks); ts.Run(timeLimit - timePenalty); TSPSolution solution = new TSPSolution(instance, ts.BestSolution); solution.Write(outputFile); }
public void Start(string fileInput, string fileOutput, int timeLimit) { TSPInstance instance = new TSPInstance(fileInput); // Setting the parameters of the GRASP for this instance of the problem. DiscreteGRASP grasp = new DiscreteGRASP2OptFirst4TSP(instance, rclThreshold); // Solving the problem and writing the best solution found. grasp.Run(timeLimit - (int)timePenalty, RunType.TimeLimit); TSPSolution solution = new TSPSolution(instance, grasp.BestSolution); solution.Write(fileOutput); }
public void Start(string inputFile, string outputFile, int timeLimit) { TSPInstance instance = new TSPInstance(inputFile); int[] lowerBounds = new int[instance.NumberCities]; int[] upperBounds = new int[instance.NumberCities]; for (int i = 0; i < instance.NumberCities; i++) { lowerBounds[i] = 0; upperBounds[i] = instance.NumberCities - 1; } DiscreteILS ils = new DiscreteILS2OptFirst4TSP(instance, restartIterations, lowerBounds, upperBounds); ils.Run(timeLimit - timePenalty); TSPSolution solution = new TSPSolution(instance, ils.BestSolution); solution.Write(outputFile); }
public void Start(string fileInput, string fileOutput, int timeLimit) { TSPInstance instance = new TSPInstance(fileInput); // Setting the parameters of the PSO for this instance of the problem. int[] lowerBounds = new int[instance.NumberCities]; int[] upperBounds = new int[instance.NumberCities]; for (int i = 0; i < instance.NumberCities; i++) { lowerBounds[i] = 0; upperBounds[i] = instance.NumberCities - 1; } DiscretePSO pso = new DiscretePSO4TSP(instance, (int)particlesCount, prevConf, neighConf, lowerBounds, upperBounds); // Solving the problem and writing the best solution found. pso.Run(timeLimit - (int)timePenalty); TSPSolution solution = new TSPSolution(instance, pso.BestPosition); solution.Write(fileOutput); }
public void Start(string fileInput, string fileOutput, int timeLimit) { TSPInstance instance = new TSPInstance(fileInput); // Setting the parameters of the MA for this instance of the problem. int[] lowerBounds = new int[instance.NumberCities]; int[] upperBounds = new int[instance.NumberCities]; for (int i = 0; i < instance.NumberCities; i++) { lowerBounds[i] = 0; upperBounds[i] = instance.NumberCities - 1; } DiscreteMA memetic = new DiscreteMA4TSP(instance, (int)popSize, mutProbability, lowerBounds, upperBounds); // Solving the problem and writing the best solution found. memetic.Run(timeLimit - (int)timePenalty); TSPSolution solution = new TSPSolution(instance, memetic.BestIndividual); solution.Write(fileOutput); }
public void Start(string inputFile, string outputFile, int timeLimit) { TSPInstance instance = new TSPInstance(inputFile); int[] lowerBounds = new int[instance.NumberCities]; int[] upperBounds = new int[instance.NumberCities]; for (int i = 0; i < instance.NumberCities; i++) { lowerBounds[i] = 0; upperBounds[i] = instance.NumberCities - 1; } DiscreteILS ils = new DiscreteILS2OptBest4TSP(instance, restartIterations, lowerBounds, upperBounds); ils.Run(timeLimit - timePenalty); TSPSolution solution = new TSPSolution(instance, ils.BestSolution); solution.Write(outputFile); }
public void Start(string fileInput, string fileOutput, int timeLimit) { TSPInstance instance = new TSPInstance(fileInput); // Setting the parameters of the UMDA for this instance of the problem. int popSize = (int) Math.Ceiling(popFactor * instance.NumberCities); int[] lowerBounds = new int[instance.NumberCities]; int[] upperBounds = new int[instance.NumberCities]; for (int i = 0; i < instance.NumberCities; i++) { lowerBounds[i] = 0; upperBounds[i] = instance.NumberCities - 1; } DiscreteUMDA umda = new DiscreteUMDA2OptFirst4TSP(instance, popSize, truncFactor, lowerBounds, upperBounds); // Solving the problem and writing the best solution found. umda.Run(timeLimit - (int)timePenalty); TSPSolution solution = new TSPSolution(instance, umda.BestIndividual); solution.Write(fileOutput); }
public void Start(string fileInput, string fileOutput, int timeLimit) { TSPInstance instance = new TSPInstance(fileInput); // Setting the parameters of the GA for this instance of the problem. int[] lowerBounds = new int[instance.NumberCities]; int[] upperBounds = new int[instance.NumberCities]; for (int i = 0; i < instance.NumberCities; i++) { lowerBounds[i] = 0; upperBounds[i] = instance.NumberCities - 1; } DiscreteGA genetic = new DiscreteGA2OptFirst4TSP(instance, (int)popSize, mutProbability, lowerBounds, upperBounds); // Solving the problem and writing the best solution found. genetic.Run(timeLimit - (int)timePenalty); TSPSolution solution = new TSPSolution(instance, genetic.BestIndividual); solution.Write(fileOutput); }
public void Start(string fileInput, string fileOutput, int timeLimit) { TSPInstance instance = new TSPInstance(fileInput); // Setting the parameters of the PSO for this instance of the problem. int[] lowerBounds = new int[instance.NumberCities]; int[] upperBounds = new int[instance.NumberCities]; for (int i = 0; i < instance.NumberCities; i++) { lowerBounds[i] = 0; upperBounds[i] = instance.NumberCities - 1; } DiscretePSO pso = new DiscretePSO2OptFirst4TSP(instance, (int)particlesCount, prevConf, neighConf, lowerBounds, upperBounds); // Solving the problem and writing the best solution found. pso.Run(timeLimit - (int)timePenalty); TSPSolution solution = new TSPSolution(instance, pso.BestPosition); solution.Write(fileOutput); }
public void Start(string fileInput, string fileOutput, int timeLimit) { TSPInstance instance = new TSPInstance(fileInput); // Setting the parameters of the UMDA for this instance of the problem. int popSize = (int)Math.Ceiling(popFactor * instance.NumberCities); int[] lowerBounds = new int[instance.NumberCities]; int[] upperBounds = new int[instance.NumberCities]; for (int i = 0; i < instance.NumberCities; i++) { lowerBounds[i] = 0; upperBounds[i] = instance.NumberCities - 1; } DiscreteUMDA umda = new DiscreteUMDA2OptBest4TSP(instance, popSize, truncFactor, lowerBounds, upperBounds); // Solving the problem and writing the best solution found. umda.Run(timeLimit - timePenalty); TSPSolution solution = new TSPSolution(instance, umda.BestIndividual); solution.Write(fileOutput); }