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Fixed a OutOfBoundException in simplex solver when some constraints are tight 

JIRA: MATH-293

git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@813301 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Luc Maisonobe 2009-09-10 08:20:28 +00:00
parent 3cf3b82b72
commit 59a0da9c4c
3 changed files with 81 additions and 14 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

55
src/main/java/org/apache/commons/math/optimization/linear/SimplexTableau.java
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@ -74,6 +74,9 @@ class SimplexTableau implements Serializable {
/** Whether to restrict the variables to non-negative values. */
private final boolean restrictToNonNegative;
/** The variables each column represents */
private final List<String> columnLabels = new ArrayList<String>();
/** Simple tableau. */
private transient RealMatrix tableau;
@ -113,6 +116,27 @@ class SimplexTableau implements Serializable {
this.numArtificialVariables = getConstraintTypeCounts(Relationship.EQ) +
getConstraintTypeCounts(Relationship.GEQ);
this.tableau = createTableau(goalType == GoalType.MAXIMIZE);
initializeColumnLabels();
}
protected void initializeColumnLabels() {
if (getNumObjectiveFunctions() == 2) {
columnLabels.add("W");
}
columnLabels.add("Z");
for (int i = 0; i < getOriginalNumDecisionVariables(); i++) {
columnLabels.add("x" + i);
}
if (!restrictToNonNegative) {
columnLabels.add("x-");
}
for (int i = 0; i < getNumSlackVariables(); i++) {
columnLabels.add("s" + i);
}
for (int i = 0; i < getNumArtificialVariables(); i++) {
columnLabels.add("a" + i);
}
columnLabels.add("RHS");
}
/**
@ -301,6 +325,10 @@ class SimplexTableau implements Serializable {
}
}
for (int i = columnsToDrop.size() - 1; i >= 0; i--) {
columnLabels.remove((int) columnsToDrop.get(i));
}
this.tableau = new Array2DRowRealMatrix(matrix);
this.numArtificialVariables = 0;
}
@ -332,12 +360,19 @@ class SimplexTableau implements Serializable {
* @return current solution
*/
protected RealPointValuePair getSolution() {
double[] coefficients = new double[getOriginalNumDecisionVariables()];
Integer negativeVarBasicRow = getBasicRow(getNegativeDecisionVariableOffset());
int negativeVarColumn = columnLabels.indexOf("x-");
Integer negativeVarBasicRow = negativeVarColumn > 0 ? getBasicRow(negativeVarColumn) : null;
double mostNegative = negativeVarBasicRow == null ? 0 : getEntry(negativeVarBasicRow, getRhsOffset());
Set<Integer> basicRows = new HashSet<Integer>();
double[] coefficients = new double[getOriginalNumDecisionVariables()];
for (int i = 0; i < coefficients.length; i++) {
Integer basicRow = getBasicRow(getNumObjectiveFunctions() + i);
int colIndex = columnLabels.indexOf("x" + i);
if (colIndex < 0) {
coefficients[i] = 0;
continue;
}
Integer basicRow = getBasicRow(colIndex);
if (basicRows.contains(basicRow)) {
// if multiple variables can take a given value
// then we choose the first and set the rest equal to 0
@ -349,7 +384,7 @@ class SimplexTableau implements Serializable {
(restrictToNonNegative ? 0 : mostNegative);
}
}
return new RealPointValuePair(coefficients, f.getValue(coefficients));
return new RealPointValuePair(coefficients, f.getValue(coefficients));
}
/**
@ -442,15 +477,6 @@ class SimplexTableau implements Serializable {
return getWidth() - 1;
}
/**
* Returns the offset of the extra decision variable added when there is a
* negative decision variable in the original problem.
* @return the offset of x-
*/
protected final int getNegativeDecisionVariableOffset() {
return getNumObjectiveFunctions() + getOriginalNumDecisionVariables();
}
/**
* Get the number of decision variables.
* <p>
@ -471,7 +497,7 @@ class SimplexTableau implements Serializable {
* @see #getNumDecisionVariables()
*/
protected final int getOriginalNumDecisionVariables() {
return restrictToNonNegative ? numDecisionVariables : numDecisionVariables - 1;
return f.getCoefficients().getDimension();
}
/**
@ -562,4 +588,5 @@ class SimplexTableau implements Serializable {
ois.defaultReadObject();
MatrixUtils.deserializeRealMatrix(this, "tableau", ois);
}
}

3
src/site/xdoc/changes.xml
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@ -39,6 +39,9 @@ The <action> type attribute can be add,update,fix,remove.
</properties>
<body>
<release version="2.1" date="TBD" description="TBD">
<action dev="luc" type="fix" issue="MATH-293" due-to="Benjamin McCann">
Fixed a OutOfBoundException in simplex solver when some constraints are tight.
</action>
<action dev="luc" type="fix" issue="MATH-291" due-to="Sebb">
Fixed misleading number formats in error messages for adaptive
stepsize integrators.

37
src/test/java/org/apache/commons/math/optimization/linear/SimplexSolverTest.java
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@ -116,6 +116,43 @@ public class SimplexSolverTest {
solver.optimize(f, constraints, GoalType.MINIMIZE, true);
}
@Test
public void testMath293() throws OptimizationException {
LinearObjectiveFunction f = new LinearObjectiveFunction(new double[] { 0.8, 0.2, 0.7, 0.3, 0.4, 0.6}, 0 );
Collection<LinearConstraint> constraints = new ArrayList<LinearConstraint>();
constraints.add(new LinearConstraint(new double[] { 1, 0, 1, 0, 1, 0 }, Relationship.EQ, 30.0));
constraints.add(new LinearConstraint(new double[] { 0, 1, 0, 1, 0, 1 }, Relationship.EQ, 30.0));
constraints.add(new LinearConstraint(new double[] { 0.8, 0.2, 0.0, 0.0, 0.0, 0.0 }, Relationship.GEQ, 10.0));
constraints.add(new LinearConstraint(new double[] { 0.0, 0.0, 0.7, 0.3, 0.0, 0.0 }, Relationship.GEQ, 10.0));
constraints.add(new LinearConstraint(new double[] { 0.0, 0.0, 0.0, 0.0, 0.4, 0.6 }, Relationship.GEQ, 10.0));
SimplexSolver solver = new SimplexSolver();
RealPointValuePair solution1 = solver.optimize(f, constraints, GoalType.MAXIMIZE, true);
Assert.assertEquals(15.7143, solution1.getPoint()[0], .0001);
Assert.assertEquals(0.0, solution1.getPoint()[1], .0001);
Assert.assertEquals(14.2857, solution1.getPoint()[2], .0001);
Assert.assertEquals(0.0, solution1.getPoint()[3], .0001);
Assert.assertEquals(0.0, solution1.getPoint()[4], .0001);
Assert.assertEquals(30.0, solution1.getPoint()[5], .0001);
Assert.assertEquals(40.57143, solution1.getValue(), .0001);
double valA = 0.8 * solution1.getPoint()[0] + 0.2 * solution1.getPoint()[1];
double valB = 0.7 * solution1.getPoint()[2] + 0.3 * solution1.getPoint()[3];
double valC = 0.4 * solution1.getPoint()[4] + 0.6 * solution1.getPoint()[5];
f = new LinearObjectiveFunction(new double[] { 0.8, 0.2, 0.7, 0.3, 0.4, 0.6}, 0 );
constraints = new ArrayList<LinearConstraint>();
constraints.add(new LinearConstraint(new double[] { 1, 0, 1, 0, 1, 0 }, Relationship.EQ, 30.0));
constraints.add(new LinearConstraint(new double[] { 0, 1, 0, 1, 0, 1 }, Relationship.EQ, 30.0));
constraints.add(new LinearConstraint(new double[] { 0.8, 0.2, 0.0, 0.0, 0.0, 0.0 }, Relationship.GEQ, valA));
constraints.add(new LinearConstraint(new double[] { 0.0, 0.0, 0.7, 0.3, 0.0, 0.0 }, Relationship.GEQ, valB));
constraints.add(new LinearConstraint(new double[] { 0.0, 0.0, 0.0, 0.0, 0.4, 0.6 }, Relationship.GEQ, valC));
RealPointValuePair solution2 = solver.optimize(f, constraints, GoalType.MAXIMIZE, true);
Assert.assertEquals(40.57143, solution2.getValue(), .0001);
}
@Test
public void testSimplexSolver() throws OptimizationException {
LinearObjectiveFunction f =