// constriction coefficient (M. Clerc)
private double constrictionCoefficient(double c1, double c2) {
double rho = c1 + c2;
// rho = 1.0 ;
if (rho <= 4) {
return 1.0;
} else {
return 2 / (2 - rho - Math.sqrt(Math.pow(rho, 2.0) - 4.0 * rho));
}
} // constrictionCoefficient
/**
* Returns the distance between two solutions in objective space.
*
* @param solutionI The first <code>Solution</code>.
* @param solutionJ The second <code>Solution</code>.
* @return the distance between solutions in objective space.
*/
public double distanceBetweenObjectives(Solution solutionI, Solution solutionJ) {
double diff; // Auxiliar var
double distance = 0.0;
// -> Calculate the euclidean distance
for (int nObj = 0; nObj < solutionI.numberOfObjectives(); nObj++) {
diff = solutionI.getObjective(nObj) - solutionJ.getObjective(nObj);
distance += Math.pow(diff, 2.0);
} // for
// Return the euclidean distance
return Math.sqrt(distance);
} // distanceBetweenObjectives.
/**
* Returns the distance between two solutions in the search space.
*
* @param solutionI The first <code>Solution</code>.
* @param solutionJ The second <code>Solution</code>.
* @return the distance between solutions.
* @throws JMException
*/
public double distanceBetweenSolutions(Solution solutionI, Solution solutionJ)
throws JMException {
// ->Obtain his decision variables
Variable[] decisionVariableI = solutionI.getDecisionVariables();
Variable[] decisionVariableJ = solutionJ.getDecisionVariables();
double diff; // Auxiliar var
double distance = 0.0;
// -> Calculate the Euclidean distance
for (int i = 0; i < decisionVariableI.length; i++) {
diff = decisionVariableI[i].getValue() - decisionVariableJ[i].getValue();
distance += Math.pow(diff, 2.0);
} // for
// -> Return the euclidean distance
return Math.sqrt(distance);
} // distanceBetweenSolutions
