/**
 * Description: Griewank function
 * X*(Optimal point):
 * X1=0
 * X2=-1
 * Y*(Optimal value)
 * Y1=3
 *
 * @ Author        Create/Modi     Note
 * Xiaofeng Xie    Dec 28, 2001
 * Xiaofeng Xie    Mar 02, 2003
 * Xiaofeng Xie    May 11, 2004
 *
 * This library is free software; you can redistribute it and/or
 * modify it under the terms of the GNU Lesser General Public
 * License as published by the Free Software Foundation; either
 * version 2.1 of the License, or (at your option) any later version.
 *
 * This library is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 * Lesser General Public License for more details.
 *
 * Please acknowledge the author(s) if you use this code in any way.
 *
 * @version 1.0
 * @Since MAOS1.0
 *
 * @References:
 * [1] Shi Y H, Eberhart R C. Empirical study of particle swarm optimization.
 * Proc. Congress on Evolutionary Computation, 1999: 1945-1950
 */

package problem.unconstrained;

import problem.*;

public class Griewank extends UnconstrainedProblemEncoder {
  private static int NX = 30; //number of variables
  public Griewank() throws Exception {
    super(NX);
    for(int i=0; i<NX; i++) {
      setDefaultXAt(i, -600, 600); //the range of each variable
    }
  }

  //calculates the objective value
  public double calcTarget(double[] VX) {
    double value1 = 0;
    double value2 = 1;
    for (int i=0; i<NX; i++) {
      value1 += Math.pow(VX[i],2)/4000.0;
      value2 *= Math.cos(VX[i]/Math.sqrt(i+1));
    }
    return value1-value2+1;
  }
}