/**
* Evaluates a solution
*
* @param solution The solution to evaluate
* @throws JMException
*/
public void evaluate(Solution solution) throws JMException {
DecisionVariables gen = solution.getDecisionVariables();
double[] x = new double[numberOfVariables_];
double[] f = new double[numberOfObjectives_];
double[] theta = new double[numberOfObjectives_ - 1];
int k = numberOfVariables_ - numberOfObjectives_ + 1;
for (int i = 0; i < numberOfVariables_; i++) x[i] = gen.variables_[i].getValue();
double g = 0.0;
for (int i = numberOfVariables_ - k; i < numberOfVariables_; i++)
g += java.lang.Math.pow(x[i], 0.1);
double t = java.lang.Math.PI / (4.0 * (1.0 + g));
theta[0] = x[0] * java.lang.Math.PI / 2;
for (int i = 1; i < (numberOfObjectives_ - 1); i++) theta[i] = t * (1.0 + 2.0 * g * x[i]);
for (int i = 0; i < numberOfObjectives_; i++) f[i] = 1.0 + g;
for (int i = 0; i < numberOfObjectives_; i++) {
for (int j = 0; j < numberOfObjectives_ - (i + 1); j++) f[i] *= java.lang.Math.cos(theta[j]);
if (i != 0) {
int aux = numberOfObjectives_ - (i + 1);
f[i] *= java.lang.Math.sin(theta[aux]);
} // if
} // for
for (int i = 0; i < numberOfObjectives_; i++) solution.setObjective(i, f[i]);
} // evaluate
/**
* Evaluates a solution
*
* @param solution The solution to evaluate
* @throws JMException
*/
public void evaluate(Solution solution) throws JMException {
DecisionVariables decisionVariables = solution.getDecisionVariables();
double[] x = new double[numberOfVariables_];
double[] fx = new double[numberOfVariables_];
double g;
double h;
double sum;
for (int i = 0; i < numberOfVariables_; i++) x[i] = decisionVariables.variables_[i].getValue();
fx[0] = x[0];
sum = 0.0;
for (int i = 1; i < numberOfVariables_; i++) sum += (x[i] * x[i] - x[0]) * (x[i] * x[i] - x[0]);
g = 1.0 + 9.0 * sum / (numberOfVariables_ - 1.0);
h = 1.0 - Math.sqrt(x[0] / g);
fx[1] = g * h;
solution.setObjective(0, fx[0]);
solution.setObjective(1, fx[1]);
} // evaluate
/**
* Perform the crossover operation
*
* @param probability Crossover probability
* @param parent1 The first parent
* @param parent2 The second parent
* @return Two offspring solutions
* @throws JMException
*/
public Solution[] doCrossover(double probability, Solution parent1, Solution parent2)
throws JMException {
Solution[] offspring = new Solution[2];
offspring[0] = new Solution(parent1);
offspring[1] = new Solution(parent2);
if (PseudoRandom.randDouble() < probability) {
int crosspoint1;
int crosspoint2;
int chromosomeLength;
DecisionVariables parent1Vars;
DecisionVariables parent2Vars;
DecisionVariables offspring1Vars;
DecisionVariables offspring2Vars;
// permutationLength = ((Permutation)parent1.getDecisionVariables().variables_[0]).getLength()
// ;
chromosomeLength = parent1.getDecisionVariables().size();
parent1Vars = parent1.getDecisionVariables();
parent2Vars = parent2.getDecisionVariables();
offspring1Vars = offspring[0].getDecisionVariables();
offspring2Vars = offspring[1].getDecisionVariables();
// STEP 1: Get two cutting points
crosspoint1 = PseudoRandom.randInt(0, chromosomeLength - 1);
crosspoint2 = PseudoRandom.randInt(0, chromosomeLength - 1);
while (crosspoint2 == crosspoint1)
crosspoint2 = PseudoRandom.randInt(0, chromosomeLength - 1);
if (crosspoint1 > crosspoint2) {
int swap;
swap = crosspoint1;
crosspoint1 = crosspoint2;
crosspoint2 = swap;
} // if
// // STEP 2: Obtain the two children
//
// for(int k = 0; k < crosspoint1; k++) {
// offspring1Vars.variables_[k] = parent1Vars.variables_[k];
// offspring2Vars.variables_[k] = parent2Vars.variables_[k];
// }
//
// for(int k = crosspoint1; k < crosspoint2; k++) {
// offspring2Vars.variables_[k] = parent1Vars.variables_[k];
// offspring1Vars.variables_[k] = parent2Vars.variables_[k];
// } // for
//
// for(int k = crosspoint2; k < chromosomeLength; k++) {
// offspring1Vars.variables_[k] = parent1Vars.variables_[k];
// offspring2Vars.variables_[k] = parent2Vars.variables_[k];
// }
// STEP 2: Obtain the two children
for (int k = 0; k < crosspoint1; k++) {
offspring1Vars.variables_[k] = parent1Vars.variables_[k].deepCopy();
offspring2Vars.variables_[k] = parent2Vars.variables_[k].deepCopy();
}
for (int k = crosspoint1; k < crosspoint2; k++) {
offspring2Vars.variables_[k] = parent1Vars.variables_[k].deepCopy();
offspring1Vars.variables_[k] = parent2Vars.variables_[k].deepCopy();
} // for
for (int k = crosspoint2; k < chromosomeLength; k++) {
offspring1Vars.variables_[k] = parent1Vars.variables_[k].deepCopy();
offspring2Vars.variables_[k] = parent2Vars.variables_[k].deepCopy();
}
Comparator dominance = new DominanceComparator();
if (((dominance.compare(parent1, parent2) != -1)
&& (crosspoint2 - crosspoint1 >= chromosomeLength / 2))
|| ((dominance.compare(parent1, parent2) == -1)
&& (crosspoint2 - crosspoint1 < chromosomeLength / 2))) {
offspring[0].setDecisionVariables(offspring1Vars);
offspring[1].setDecisionVariables(offspring2Vars);
} else if (((dominance.compare(parent2, parent1) != -1)
&& (crosspoint2 - crosspoint1 >= chromosomeLength / 2))
|| ((dominance.compare(parent2, parent1) == -1)
&& (crosspoint2 - crosspoint1 < chromosomeLength / 2))) {
offspring[1].setDecisionVariables(offspring1Vars);
offspring[0].setDecisionVariables(offspring2Vars);
}
// else
// {
// Configuration.logger_.severe("TwoPointsCrossover.doCrossover: invalid " +
// "type" +
// parent1.getDecisionVariables().variables_[0].getVariableType());
// Class cls = java.lang.String.class;
// String name = cls.getName();
// throw new JMException("Exception in " + name + ".doCrossover()") ;
// } // else
}
return offspring;
} // makeCrossover