Example usage for org.apache.commons.math3.optim.linear PivotSelectionRule BLAND

Introduction

In this page you can find the example usage for org.apache.commons.math3.optim.linear PivotSelectionRule BLAND.

Prototype

PivotSelectionRule BLAND

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Document

The first variable with a negative coefficient in the objective function row will be chosen as entering variable.

Usage

From source file:com.datumbox.framework.core.mathematics.linearprogramming.LPSolver.java

/**
 * Solves the LP problem and returns the result.
 * //from w  w w . j ava2 s .c o  m
 * @param linearObjectiveFunction
 * @param linearConstraintsList
 * @param nonNegative
 * @param maximize
 * @return
 */
public static LPResult solve(double[] linearObjectiveFunction,
        List<LPSolver.LPConstraint> linearConstraintsList, boolean nonNegative, boolean maximize) {
    int m = linearConstraintsList.size();

    List<LinearConstraint> constraints = new ArrayList<>(m);
    for (LPSolver.LPConstraint constraint : linearConstraintsList) {
        String sign = constraint.getSign();
        Relationship relationship = null;
        if (LPSolver.GEQ.equals(sign)) {
            relationship = Relationship.GEQ;
        } else if (LPSolver.LEQ.equals(sign)) {
            relationship = Relationship.LEQ;
        } else if (LPSolver.EQ.equals(sign)) {
            relationship = Relationship.EQ;
        }
        constraints
                .add(new LinearConstraint(constraint.getContraintBody(), relationship, constraint.getValue()));
    }

    SimplexSolver solver = new SimplexSolver();
    PointValuePair solution = solver.optimize(new LinearObjectiveFunction(linearObjectiveFunction, 0.0),
            new LinearConstraintSet(constraints), maximize ? GoalType.MAXIMIZE : GoalType.MINIMIZE,
            new NonNegativeConstraint(nonNegative), PivotSelectionRule.BLAND);

    LPResult result = new LPResult();
    result.setObjectiveValue(solution.getValue());
    result.setVariableValues(solution.getPoint());

    return result;
}

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