Reputation: 455
I am working on solving a linear programming problem using joptimizer.
My problem is:
Maximize (x1*f1 + x2*f2 + x3*f3)
such that (x1*v1 + x2*v2 + x3*v3) <= h
I need to find x1, x2 and x3.
I do not know how to create a joptimizer input from the above equation.
Upvotes: 3
Views: 3391
Reputation: 1581
Maybe you would like to have a look at the following sample code too.
Don't forget to import the dependecies from http://www.joptimizer.com/downloadWithAdd.html.
You should download and import external three jar files ( /joptimizer-4.0.0.jar
, /joptimizer-4.0.0-dependencies.zip
, /joptimizer-4.0.0-sources.jar
) into your project manually. The .zip
file demands unzipping too.
import java.util.Arrays;
import com.joptimizer.optimizers.*;
public class LCLP {
// min (x) for J = C'*X;
// s.t.
// A*X = b;
// X <= 0;
// X = [x1;x2;x3;...xN]
public static void main(String[] args) throws Exception {
// Example from http://www.joptimizer.com/linearProgramming.html
//Objective function
double[] c = new double[] { -1., -1. };
//Inequalities constraints
double[][] G = new double[][] {{4./3., -1}, {-1./2., 1.}, {-2., -1.}, {1./3., 1.}};
double[] h = new double[] {2., 1./2., 2., 1./2.};
//Bounds on variables
double[] lb = new double[] {0 , 0};
double[] ub = new double[] {10, 10};
//optimization problem
LPOptimizationRequest or = new LPOptimizationRequest();
or.setC(c);
or.setG(G);
or.setH(h);
or.setLb(lb);
or.setUb(ub);
or.setDumpProblem(true);
//optimization
LPPrimalDualMethod opt = new LPPrimalDualMethod();
opt.setLPOptimizationRequest(or);
opt.optimize();
double[] sol = opt.getOptimizationResponse().getSolution();
System.out.println("Solution = " + Arrays.toString(sol));
}
}
Upvotes: -1
Reputation: 1235
Java doc is available here http://www.joptimizer.com/apidocs/index.html
simple example minimize 3x+4y such that 2x+3y >= 8, 5x+2y >= 12, x >= 0, y >= 0
My sample code for solving simple linear programming question is below:
package test_joptimizer;
import com.joptimizer.functions.ConvexMultivariateRealFunction;
import com.joptimizer.functions.LinearMultivariateRealFunction;
import com.joptimizer.optimizers.JOptimizer;
import com.joptimizer.optimizers.OptimizationRequest;
import org.apache.log4j.BasicConfigurator;
/**
* @author K.P.L.Kanchana
*/
public class Main {
public static void main(String[] args) throws Exception {
// Objective function (plane)
LinearMultivariateRealFunction objectiveFunction = new LinearMultivariateRealFunction(new double[] {3.0, 4.0}, 0); //minimize 3x+4y
//inequalities (polyhedral feasible set G.X<H )
ConvexMultivariateRealFunction[] inequalities = new ConvexMultivariateRealFunction[4];
// x >= 0
inequalities[0] = new LinearMultivariateRealFunction(new double[]{-1.0, 0.00}, 0.0); // focus: -x+0 <= 0
// y >= 0
inequalities[1] = new LinearMultivariateRealFunction(new double[]{0.0, -1.00}, 0.0); // focus: -y+0 <= 0
// 2x+3y >= 8
inequalities[2] = new LinearMultivariateRealFunction(new double[]{-2.0, -3.00}, 8.0); // focus: -2x-3y+8 <= 0
// 5x+2y >= 12
inequalities[3] = new LinearMultivariateRealFunction(new double[]{-5.0, -2.00}, 12.0);// focus: -5x-2y+12 <= 0
//optimization problem
OptimizationRequest or = new OptimizationRequest();
or.setF0(objectiveFunction);
or.setFi(inequalities);
//or.setInitialPoint(new double[] {0.0, 0.0});//initial feasible point, not mandatory
or.setToleranceFeas(1.E-9);
or.setTolerance(1.E-9);
//optimization
JOptimizer opt = new JOptimizer();
opt.setOptimizationRequest(or);
int returnCode = opt.optimize();
double[] sol = opt.getOptimizationResponse().getSolution();
System.out.println("Length: " + sol.length);
for (int i=0; i<sol.length/2; i++){
System.out.println( "X" + (i+1) + ": " + Math.round(sol[i]) + "\ty" + (i+1) + ": " + Math.round(sol[i+1]) );
}
}
}
Upvotes: 3