Examples of ObjectiveFunction

org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunction
Scalar function to be optimized. @since 3.1
org.sat4j.pb.ObjectiveFunction
rinde.sim.pdptw.common.ObjectiveFunction
Instances of this interface define an objective on which a {@link StatisticsDTO} can be measured.
Implementations should not keep any internal state. @author Rinde van Lon

Examples of org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunction

    @Test(expected=TooManyEvaluationsException.class)
    public void testMaxIterations() {
        Powell powell = new Powell();
        SimplexOptimizer optimizer = new SimplexOptimizer(-1, 1e-3);
        optimizer.optimize(new MaxEval(20),
                           new ObjectiveFunction(powell),
                           GoalType.MINIMIZE,
                           new InitialGuess(new double[] { 3, -1, 0, 1 }),
                           new NelderMeadSimplex(4));
    }

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Examples of org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunction

        final double[] start = { 0 };
        final double[] lower = { -1e6 };
        final double[] upper = { 1.5 };
        final double[] sigma = { 1e-1 };
        final double[] result = optimizer.optimize(new MaxEval(10000),
                                                   new ObjectiveFunction(fitnessFunction),
                                                   GoalType.MINIMIZE,
                                                   new CMAESOptimizer.PopulationSize(5),
                                                   new CMAESOptimizer.Sigma(sigma),
                                                   new InitialGuess(start),
                                                   new SimpleBounds(lower, upper)).getPoint();

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Examples of org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunction


        final double[] start = { 1 };
 
        // No bounds.
        PointValuePair result = optimizer.optimize(new MaxEval(100000),
                                                   new ObjectiveFunction(fitnessFunction),
                                                   GoalType.MINIMIZE,
                                                   SimpleBounds.unbounded(1),
                                                   new CMAESOptimizer.PopulationSize(5),
                                                   new CMAESOptimizer.Sigma(new double[] { 1e-1 }),
                                                   new InitialGuess(start));
        final double resNoBound = result.getPoint()[0];


        // Optimum is near the lower bound.
        final double[] lower = { -20 };
        final double[] upper = { 5e16 };
        final double[] sigma = { 10 };
        result = optimizer.optimize(new MaxEval(100000),
                                    new ObjectiveFunction(fitnessFunction),
                                    GoalType.MINIMIZE,
                                    new CMAESOptimizer.PopulationSize(5),
                                    new CMAESOptimizer.Sigma(sigma),
                                    new InitialGuess(start),
                                    new SimpleBounds(lower, upper));
        final double resNearLo = result.getPoint()[0];


        // Optimum is near the upper bound.
        lower[0] = -5e16;
        upper[0] = 20;
        result = optimizer.optimize(new MaxEval(100000),
                                    new ObjectiveFunction(fitnessFunction),
                                    GoalType.MINIMIZE,
                                    new CMAESOptimizer.PopulationSize(5),
                                    new CMAESOptimizer.Sigma(sigma),
                                    new InitialGuess(start),
                                    new SimpleBounds(lower, upper));

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Examples of org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunction

        // test diagonalOnly = 0 - slow but normally fewer feval#
        CMAESOptimizer optim = new CMAESOptimizer(30000, stopValue, isActive, diagonalOnly,
                                                  0, new MersenneTwister(), false, null);
        PointValuePair result = boundaries == null ?
            optim.optimize(new MaxEval(maxEvaluations),
                           new ObjectiveFunction(func),
                           goal,
                           new InitialGuess(startPoint),
                           SimpleBounds.unbounded(dim),
                           new CMAESOptimizer.Sigma(inSigma),
                           new CMAESOptimizer.PopulationSize(lambda)) :
            optim.optimize(new MaxEval(maxEvaluations),
                           new ObjectiveFunction(func),
                           goal,
                           new SimpleBounds(boundaries[0],
                                            boundaries[1]),
                           new InitialGuess(startPoint),
                           new CMAESOptimizer.Sigma(inSigma),

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Examples of org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunction

        int dim = startPoint.length;
        final int numIterpolationPoints = 2 * dim + 1 + additionalInterpolationPoints;
        BOBYQAOptimizer optim = new BOBYQAOptimizer(numIterpolationPoints);
        PointValuePair result = boundaries == null ?
            optim.optimize(new MaxEval(maxEvaluations),
                           new ObjectiveFunction(func),
                           goal,
                           SimpleBounds.unbounded(dim),
                           new InitialGuess(startPoint)) :
            optim.optimize(new MaxEval(maxEvaluations),
                           new ObjectiveFunction(func),
                           goal,
                           new InitialGuess(startPoint),
                           new SimpleBounds(boundaries[0],
                                            boundaries[1]));
//        System.out.println(func.getClass().getName() + " = "

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Examples of org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunction

            this.factors = new BlockRealMatrix(factors);
            this.target  = target;
        }


        public ObjectiveFunction getObjectiveFunction() {
            return new ObjectiveFunction(new MultivariateFunction() {
                    public double value(double[] point) {
                        double[] y = factors.operate(point);
                        double sum = 0;
                        for (int i = 0; i < y.length; ++i) {
                            double ri = y[i] - target[i];

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Examples of org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunction

    public void testBoundsUnsupported() {
        SimplexOptimizer optimizer = new SimplexOptimizer(1e-10, 1e-30);
        final FourExtrema fourExtrema = new FourExtrema();


        optimizer.optimize(new MaxEval(100),
                           new ObjectiveFunction(fourExtrema),
                           GoalType.MINIMIZE,
                           new InitialGuess(new double[] { -3, 0 }),
                           new NelderMeadSimplex(new double[] { 0.2, 0.2 }),
                           new SimpleBounds(new double[] { -5, -1 },
                                            new double[] { 5, 1 }));

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Examples of org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunction

        SimplexOptimizer optimizer = new SimplexOptimizer(1e-11, 1e-30);
        final FourExtrema fourExtrema = new FourExtrema();


        final PointValuePair optimum
            = optimizer.optimize(new MaxEval(200),
                                 new ObjectiveFunction(fourExtrema),
                                 GoalType.MINIMIZE,
                                 new InitialGuess(new double[] { -3, 0 }),
                                 new MultiDirectionalSimplex(new double[] { 0.2, 0.2 }));
        Assert.assertEquals(fourExtrema.xM, optimum.getPoint()[0], 4e-6);
        Assert.assertEquals(fourExtrema.yP, optimum.getPoint()[1], 3e-6);

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Examples of org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunction

        SimplexOptimizer optimizer = new SimplexOptimizer(1e-11, 1e-30);
        final FourExtrema fourExtrema = new FourExtrema();


        final PointValuePair optimum
            = optimizer.optimize(new MaxEval(200),
                                 new ObjectiveFunction(fourExtrema),
                                 GoalType.MINIMIZE,
                                 new InitialGuess(new double[] { 1, 0 }),
                                 new MultiDirectionalSimplex(new double[] { 0.2, 0.2 }));
        Assert.assertEquals(fourExtrema.xP, optimum.getPoint()[0], 2e-8);
        Assert.assertEquals(fourExtrema.yM, optimum.getPoint()[1], 3e-6);

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Examples of org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunction

        SimplexOptimizer optimizer = new SimplexOptimizer(1e-11, 1e-30);
        final FourExtrema fourExtrema = new FourExtrema();


        final PointValuePair optimum
            = optimizer.optimize(new MaxEval(200),
                                 new ObjectiveFunction(fourExtrema),
                                 GoalType.MAXIMIZE,
                                 new InitialGuess(new double[] { -3.0, 0.0 }),
                                 new MultiDirectionalSimplex(new double[] { 0.2, 0.2 }));
        Assert.assertEquals(fourExtrema.xM, optimum.getPoint()[0], 7e-7);
        Assert.assertEquals(fourExtrema.yM, optimum.getPoint()[1], 3e-7);

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