public void initiateVars() {
GaMain =
new singleThreadGAwithEDA(); // singleThreadGA singleThreadGAwithSecondFront
// singleThreadGAwithMultipleCrossover adaptiveGA
Population = new population();
Selection = new binaryTournament(); // binaryTournament
Crossover =
new twoPointCrossover2EDA(); // twoPointCrossover2 oneByOneChromosomeCrossover
// twoPointCrossover2withAdpative
// twoPointCrossover2withAdpativeThreshold
Mutation =
new swapMutationEDA(); // shiftMutation shiftMutationWithAdaptive
// shiftMutationWithAdaptiveThreshold
ObjectiveFunction = new ObjectiveFunctionTSPI[numberOfObjs];
ObjectiveFunction[0] = new ObjectiveFunctionMTSPHeu();
Fitness = new singleObjectiveFitness();
objectiveMinimization = new boolean[numberOfObjs];
objectiveMinimization[0] = true;
encodeType = true;
if (numberOfSalesmen >= length) {
System.out.println(
"The number of salesmen is "
+ numberOfSalesmen
+ ", which should be greater than the number of visiting locations.");
System.out.println("The program will exit.");
System.exit(0);
}
localSearch1 = new localSearchBy2OptForMTSP();
// localSearch1.setMTSPData(Population, distanceMatrix, numberOfSalesmen);
ObjectiveFunction[0].setTSPData(originalPoint, coordinates, numberOfSalesmen);
ObjectiveFunction[0].setObjectiveFunctionType("TotalDistance");
// set the data to the GA main program.
GaMain.setData(
Population,
Selection,
Crossover,
Mutation,
ObjectiveFunction,
Fitness,
DEFAULT_generations,
DEFAULT_PopSize,
DEFAULT_PopSize,
length,
DEFAULT_crossoverRate,
DEFAULT_mutationRate,
objectiveMinimization,
numberOfObjs,
encodeType,
elitism);
GaMain.setLocalSearchOperator(localSearch1, applyLocalSearch, 20);
GaMain.setSecondaryCrossoverOperator(Crossover2, false);
GaMain.setSecondaryMutationOperator(Mutation2, false);
GaMain.setEDAinfo(
lamda, numberOfCrossoverTournament, numberOfMutationTournament, startingGenDividen);
}
