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📄 cec2009_uf4.java

📁 关于多目标优化的代码
💻 JAVA
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/** * CEC2009_UF4.java * * @author Antonio J. Nebro * @version 1.0 */package jmetal.problems.cec2009Competition;import jmetal.base.*;import jmetal.base.Configuration.SolutionType_;import jmetal.base.Configuration.VariableType_;import jmetal.util.JMException;/** * Class representing problem CEC2009_UF4 */public class CEC2009_UF4 extends Problem {     /**   * Constructor.  * Creates a default instance of problem CEC2009_UF4 (30 decision variables)  * @param solutionType The solution type must "Real" or "BinaryReal".  */  public CEC2009_UF4(String solutionType) {    this(30, solutionType); // 30 variables by default  } // CEC2009_UF1   /**  * Creates a new instance of problem CEC2009_UF4.  * @param numberOfVariables Number of variables.  * @param solutionType The solution type must "Real" or "BinaryReal".  */  public CEC2009_UF4(Integer numberOfVariables, String solutionType) {    numberOfVariables_  = numberOfVariables.intValue();    numberOfObjectives_ =  2;    numberOfConstraints_=  0;    problemName_        = "CEC2009_UF4";    upperLimit_ = new double[numberOfVariables_];    lowerLimit_ = new double[numberOfVariables_];    // Establishes upper and lower limits for the variables    for (int var = 0; var < numberOfVariables_; var++)    {      lowerLimit_[var] = 0.0;      upperLimit_[var] = 1.0;    } // for    solutionType_ = Enum.valueOf(SolutionType_.class, solutionType) ;         // All the variables are of the same type, so the solutionType name is the    // same than the variableType name    variableType_ = new VariableType_[numberOfVariables_];    for (int var = 0; var < numberOfVariables_; var++){      variableType_[var] = Enum.valueOf(VariableType_.class, solutionType) ;        } // for  } // CEC2009_UF4      /**    * 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_] ;    for (int i = 0; i < numberOfVariables_; i++)      x[i] = decisionVariables.variables_[i].getValue() ;  	int count1, count2;		double sum1, sum2, yj, hj ;		sum1   = sum2   = 0.0;		count1 = count2 = 0;        for (int j = 2 ; j <= numberOfVariables_; j++) {			yj = x[j-1]-Math.sin(6.0*Math.PI*x[0]+j*Math.PI/numberOfVariables_);			hj = Math.abs(yj)/(1.0+Math.exp(2.0*Math.abs(yj)));			if (j % 2 == 0) {				sum2  += hj;				count2++;			} else {				sum1  += hj;				count1++;			}    }        solution.setObjective(0, x[0]	+ 2.0*sum1 / (double)count1);    solution.setObjective(1, 1.0 - x[0]*x[0]	+ 2.0*sum2 / (double)count2);  } // evaluate} // CEC2009_UF4

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