Example usage for org.apache.commons.math3.linear FieldVector setEntry

Introduction

In this page you can find the example usage for org.apache.commons.math3.linear FieldVector setEntry.

Prototype

void setEntry(int index, T value) throws OutOfRangeException;

Source Link

Document

Set a single element.

Usage

From source file:model.LP.java

/**
 * Do one iteration of the simplex method.
 *
 * @param  entering//ww  w .j a v  a  2s  .c om
 *         Index of variable to enter the basis.
 * @param  leaving
 *         Index of variable to leave the basis.
 * @return
 *         A linear program after one iteration.
 */
public LP pivot(int entering, int leaving) {
    FieldMatrix<BigFraction> bin = new FieldLUDecomposition<BigFraction>(B_).getSolver().getInverse()
            .multiply(N_);

    // Step 1: Check for optimpivality
    // Step 2: Select entering variable.
    // Naive method. Does not check for optimality. Assumes feasibility.
    // Entering variable is given.

    // Step 3: Compute primal step direction.
    FieldVector<BigFraction> ej = new ArrayFieldVector<BigFraction>(bin.getColumnDimension(), BigFraction.ZERO);
    ej.setEntry(entering, BigFraction.ONE);
    FieldVector<BigFraction> psd = bin.operate(ej);

    // Step 4: Compute primal step length.
    // Step 5: Select leaving variable.
    // Leaving variable is given.
    BigFraction t = b_.getEntry(leaving).divide(psd.getEntry(leaving));

    // Step 6: Compute dual step direction.
    FieldVector<BigFraction> ei = new ArrayFieldVector<BigFraction>(bin.getRowDimension(), BigFraction.ZERO);
    ei.setEntry(leaving, BigFraction.ONE);
    FieldVector<BigFraction> dsd = bin.transpose().scalarMultiply(BigFraction.MINUS_ONE).operate(ei);

    // Step 7: Compute dual step length.
    BigFraction s = c_.getEntry(entering).divide(dsd.getEntry(entering));

    // Step 8: Update current primal and dual solutions.
    FieldVector<BigFraction> nb_ = b_.subtract(psd.mapMultiply(t));
    nb_.setEntry(leaving, t);

    FieldVector<BigFraction> nc_ = c_.subtract(dsd.mapMultiply(s));
    nc_.setEntry(entering, s);

    // Step 9: Update basis.
    FieldVector<BigFraction> temp = B_.getColumnVector(leaving);
    FieldMatrix<BigFraction> nB_ = B_.copy();
    nB_.setColumn(leaving, N_.getColumn(entering));

    FieldMatrix<BigFraction> nN_ = N_.copy();
    nN_.setColumnVector(entering, temp);

    int[] nBi = Bi.clone();
    int[] nNi = Ni.clone();
    nBi[leaving] = Ni[entering];
    nNi[entering] = Bi[leaving];

    return new LP(B, N, b, c, nB_, nN_, nb_, nc_, x, nBi, nNi);
}

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From source file:model.LP.java

/**
 * Find a leaving variable index that is the most
 * bounding on the given entering variable index.
 *
 * @param  entering//from  w  w  w .j a v a2s . c o m
 *         an entering variable index.
 * @param  dual
 *         If true, find a leaving variable index for the dual dictionary.
 *         Otherwise, find one for the primal dictionary.
 * @return
 *         A leaving variable index.
 */
private int leaving(int entering, boolean dual) {
    FieldVector<BigFraction> check;
    FieldVector<BigFraction> sd;

    FieldMatrix<BigFraction> bin = new FieldLUDecomposition<BigFraction>(B_).getSolver().getInverse()
            .multiply(N_);

    if (dual) {
        check = c_;
        FieldVector<BigFraction> unit = new ArrayFieldVector<BigFraction>(bin.getRowDimension(),
                BigFraction.ZERO);
        unit.setEntry(entering, BigFraction.ONE);
        sd = bin.transpose().scalarMultiply(BigFraction.MINUS_ONE).operate(unit);
    } else {
        check = b_;
        FieldVector<BigFraction> unit = new ArrayFieldVector<BigFraction>(bin.getColumnDimension(),
                BigFraction.ZERO);
        unit.setEntry(entering, BigFraction.ONE);
        sd = bin.operate(unit);
    }

    boolean unbounded = true;
    int index = -1;

    /* Check for unboundedness and find first non-zero element in check */
    for (int i = 0; i < sd.getDimension(); i++) {
        if (!check.getEntry(i).equals(BigFraction.ZERO) && index == -1) {
            index = i;
        }
        if (sd.getEntry(i).compareTo(BigFraction.ZERO) > 0) {
            unbounded = false;
        }
    }
    String e = "Program is unbounded.";
    if (unbounded)
        throw new RuntimeException(e);

    /* Set temporarily max value as ratio of the first divisible pair. */
    BigFraction max = sd.getEntry(index).divide(check.getEntry(index));

    for (int i = 0; i < sd.getDimension(); i++) {
        BigFraction num = sd.getEntry(i);
        BigFraction denom = check.getEntry(i);

        if (!denom.equals(BigFraction.ZERO)) {
            BigFraction val = num.divide(denom);
            if (val.compareTo(max) > 0) {
                max = val;
                index = i;
            }
        } else {
            if (num.compareTo(BigFraction.ZERO) > 0)
                return i;
        }
    }

    return index;
}

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From source file:model.LP.java

public LP reinstate() {
    FieldVector<BigFraction> nc_ = new ArrayFieldVector<BigFraction>(c_.getDimension(), BigFraction.ZERO);
    FieldMatrix<BigFraction> bin = new FieldLUDecomposition<BigFraction>(B_).getSolver().getInverse()
            .multiply(N_);//from   w w  w  . ja  v  a2s.  c  o m

    for (int i = 0; i < Bi.length; i++) {
        int k = Bi[i];
        if (k < Ni.length) {
            for (int j = 0; j < Ni.length; j++) {
                BigFraction bf = c.getEntry(k).multiply(bin.getEntry(i, j));
                nc_.setEntry(j, nc_.getEntry(j).add(bf));
            }
        }
    }

    for (int i = 0; i < Ni.length; i++) {
        int k = Ni[i];
        if (k < Ni.length) {
            nc_.setEntry(i, nc_.getEntry(i).subtract(c.getEntry(i)));
        }
    }

    return new LP(B, N, b, c, B_, N_, b_, nc_, x, Bi, Ni);
}

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