ZeroOneILPProblem (LBJava 1.2.22 API)

java.lang.Object
- edu.illinois.cs.cogcomp.lbjava.infer.ZeroOneILPProblem

Direct Known Subclasses:

BalasHook
```
public class ZeroOneILPProblem
extends Object
```
Can be used to represent an ILP problem, assuming all variables are 0-1.

Author:

Nick Rizzolo

Field Summary

Fields
Modifier and Type	Field and Description
`protected edu.illinois.cs.cogcomp.core.datastructures.vectors.DVector2D`	`Ac` Half of a sparse matrix representation of the constraints; this half contains the coefficients on the variables whose indexes appear in `Av`.
`protected edu.illinois.cs.cogcomp.core.datastructures.vectors.IVector2D`	`Av` Half of a sparse matrix representation of the constraints; this half contains the variable indexes corresponding to the coefficients in `Ac`.
`protected edu.illinois.cs.cogcomp.core.datastructures.vectors.DVector`	`bounds` The vector of constraint bounds.
`protected edu.illinois.cs.cogcomp.core.datastructures.vectors.IVector`	`boundTypes` Contains the types of the constraints.
`static String[]`	`boundTypeSymbols` Maps from the three constraint types to their operator symbols.
`static int`	`EQUALITY` Represents the constraint type "equality".
`static int`	`GREATER_THAN` Represents the constraint type "greater than or equal to".
`static int`	`LESS_THAN` Represents the constraint type "less than or equal to".
`protected boolean`	`maximize` Remembers whether the objective function should be maximized or minimzed.
`protected edu.illinois.cs.cogcomp.core.datastructures.vectors.DVector`	`objectiveCoefficients` Represents the coefficients of all inference variables in the objective function.
`static double`	`TOLERANCE` Used to mitigate floating point error in (in)equality comparisons.

Constructor Summary

Constructors
Constructor and Description
`ZeroOneILPProblem()` Default constructor.
`ZeroOneILPProblem(String name)` Reads a textual representation of a 0-1 ILP problem from the specified file.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`int`	`addBooleanVariable(double c)` Adds a new Boolean variable (an integer variable constrained to take either the value 0 or the value 1) with the specified coefficient in the objective function to the problem.
`protected void`	`addConstraint(int[] I, double[] a, double b)` Adds a typeless constraint to the problem.
`protected void`	`addConstraint(int[] i, double[] a, int t, double b)` Adds a new constraint of the specified type to the problem.
`int[]`	`addDiscreteVariable(double[] c)` Adds a general, multi-valued discrete variable, which is implemented as a set of Boolean variables, one per value of the discrete variable, with exactly one of those variables set `true` at any given time.
`int[]`	`addDiscreteVariable(Score[] c)` Adds a general, multi-valued discrete variable, which is implemented as a set of Boolean variables, one per value of the discrete variable, with exactly one of those variables set `true` at any given time.
`void`	`addEqualityConstraint(int[] i, double[] a, double b)` Adds a new fixed constraint to the problem.
`void`	`addGreaterThanConstraint(int[] i, double[] a, double b)` Adds a new lower bounded constraint to the problem.
`void`	`addLessThanConstraint(int[] i, double[] a, double b)` Adds a new upper bounded constraint to the problem.
`int`	`columns()` Returns the number of variables in the ILP problem.
`boolean`	`constraintsSatisfied(int[] x)` Determines whether all constraints are satisfied by the given solution.
`double`	`evaluate(int[] x)` This method evaluates the objective function on a potential (not necessarily feasible) solution.
`int`	`getBoundType(int i)` Returns the type of the specified constraint's bound.
`double`	`getConstraintBound(int i)` Returns the bound of the specified constraint.
`double`	`getConstraintCoefficient(int i, int j)` Returns the specified constraint coefficient.
`boolean`	`getMaximize()` Returns `true` iff the objective function is to be maximized.
`double`	`getObjectiveCoefficient(int j)` Returns the specified objective coefficient.
`void`	`reset()` This method clears the all constraints and variables out of the problem representation, bringing it back to the state it was in when first constructed.
`int`	`rows()` Returns the number of constraints in the ILP problem.
`void`	`setBoundType(int i, int t)` Sets the bound type for the specified constraint.
`void`	`setConstraintBound(int i, double bi)` Sets the bound on the specified constraint.
`void`	`setConstraintCoefficient(int i, int j, double aij)` Sets the specified coefficient in the constraint matrix.
`void`	`setMaximize(boolean d)` Sets the direction of the objective function.
`void`	`setObjectiveCoefficient(int j, double cj)` Sets the specified coefficient in the objective function.
`String`	`toString()` Returns the representation created by `write(StringBuffer)`.
`void`	`write(StringBuffer buffer)` Creates a textual representation of the ILP problem in an algebraic notation.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

- Field Detail
  - EQUALITY
```
public static final int EQUALITY
```
    Represents the constraint type "equality".
    
    See Also:
    
    Constant Field Values
  - LESS_THAN
```
public static final int LESS_THAN
```
    Represents the constraint type "less than or equal to".
    
    See Also:
    
    Constant Field Values
  - GREATER_THAN
```
public static final int GREATER_THAN
```
    Represents the constraint type "greater than or equal to".
    
    See Also:
    
    Constant Field Values
  - boundTypeSymbols
```
public static final String[] boundTypeSymbols
```
    Maps from the three constraint types to their operator symbols.
  - TOLERANCE
```
public static final double TOLERANCE
```
    Used to mitigate floating point error in (in)equality comparisons.
    
    See Also:
    
    Constant Field Values
  - maximize
```
protected boolean maximize
```
    Remembers whether the objective function should be maximized or minimzed.
  - objectiveCoefficients
```
protected edu.illinois.cs.cogcomp.core.datastructures.vectors.DVector objectiveCoefficients
```
    Represents the coefficients of all inference variables in the objective function.
  - Av
```
protected edu.illinois.cs.cogcomp.core.datastructures.vectors.IVector2D Av
```
    Half of a sparse matrix representation of the constraints; this half contains the variable indexes corresponding to the coefficients in Ac.
  - Ac
```
protected edu.illinois.cs.cogcomp.core.datastructures.vectors.DVector2D Ac
```
    Half of a sparse matrix representation of the constraints; this half contains the coefficients on the variables whose indexes appear in Av.
  - boundTypes
```
protected edu.illinois.cs.cogcomp.core.datastructures.vectors.IVector boundTypes
```
    Contains the types of the constraints.
  - bounds
```
protected edu.illinois.cs.cogcomp.core.datastructures.vectors.DVector bounds
```
    The vector of constraint bounds.
- Constructor Detail
  - ZeroOneILPProblem
```
public ZeroOneILPProblem()
```
    Default constructor.
  - ZeroOneILPProblem
```
public ZeroOneILPProblem(String name)
```
    Reads a textual representation of a 0-1 ILP problem from the specified file.
    
    Parameters:
    
    name - The name of the file from which to read the ILP problem's representation.
- Method Detail
  - reset
```
public void reset()
```
    This method clears the all constraints and variables out of the problem representation, bringing it back to the state it was in when first constructed.
  - setMaximize
```
public void setMaximize(boolean d)
```
    Sets the direction of the objective function.
    
    Parameters:
    
    d - true if the objective function is to be maximized.
  - getMaximize
```
public boolean getMaximize()
```
    Returns true iff the objective function is to be maximized.
  - rows
```
public int rows()
```
    Returns the number of constraints in the ILP problem.
  - columns
```
public int columns()
```
    Returns the number of variables in the ILP problem.
  - setObjectiveCoefficient
```
public void setObjectiveCoefficient(int j,
                                    double cj)
```
    Sets the specified coefficient in the objective function.
    
    Parameters:
    
    j - The index of the variable whose coefficient will be set.
    
    cj - The new value of the coefficient.
  - getObjectiveCoefficient
```
public double getObjectiveCoefficient(int j)
```
    Returns the specified objective coefficient.
  - setConstraintCoefficient
```
public void setConstraintCoefficient(int i,
                                     int j,
                                     double aij)
```
    Sets the specified coefficient in the constraint matrix.
    
    Parameters:
    
    i - The index of the constraint.
    
    j - The index of the variable.
    
    aij - The new value of the coefficient.
  - getConstraintCoefficient
```
public double getConstraintCoefficient(int i,
                                       int j)
```
    Returns the specified constraint coefficient.
  - setBoundType
```
public void setBoundType(int i,
                         int t)
```
    Sets the bound type for the specified constraint.
    
    Parameters:
    
    i - The constraint whose bound type will be set.
    
    t - The new type for the constraint's bound.
  - getBoundType
```
public int getBoundType(int i)
```
    Returns the type of the specified constraint's bound.
  - setConstraintBound
```
public void setConstraintBound(int i,
                               double bi)
```
    Sets the bound on the specified constraint.
    
    Parameters:
    
    i - The constraint whose bound will be set.
    
    bi - The new value for the bound.
  - getConstraintBound
```
public double getConstraintBound(int i)
```
    Returns the bound of the specified constraint.
  - constraintsSatisfied
```
public boolean constraintsSatisfied(int[] x)
```
    Determines whether all constraints are satisfied by the given solution.
    
    Parameters:
    
    x - The settings of the variables.
    
    Returns:
    
    true iff all constraints are satisfied.
  - addBooleanVariable
```
public int addBooleanVariable(double c)
```
    Adds a new Boolean variable (an integer variable constrained to take either the value 0 or the value 1) with the specified coefficient in the objective function to the problem.
    
    Parameters:
    
    c - The objective function coefficient for the new Boolean variable.
    
    Returns:
    
    The index of the created variable.
  - addDiscreteVariable
```
public int[] addDiscreteVariable(double[] c)
```
    Adds a general, multi-valued discrete variable, which is implemented as a set of Boolean variables, one per value of the discrete variable, with exactly one of those variables set true at any given time.
    
    Parameters:
    
    c - The objective function coefficients for the new Boolean variables.
    
    Returns:
    
    The indexes of the newly created variables.
  - addDiscreteVariable
```
public int[] addDiscreteVariable(Score[] c)
```
    Adds a general, multi-valued discrete variable, which is implemented as a set of Boolean variables, one per value of the discrete variable, with exactly one of those variables set true at any given time.
    
    Parameters:
    
    c - An array of Scores containing the objective function coefficients for the new Boolean variables.
    
    Returns:
    
    The indexes of the newly created variables.
  - addConstraint
```
protected void addConstraint(int[] I,
                             double[] a,
                             double b)
```
    Adds a typeless constraint to the problem. No need to waste space storing the types of constraints if they are implied or assumed. Otherwise, this method does the same thing as addConstraint(int[],double[],int,double).
    
    Parameters:
    
    I - The indexes of the variables with non-zero coefficients.
    
    a - The coefficients of the variables with the given indexes.
    
    b - The new constraint will enforce equality with this constant.
  - addConstraint
```
protected void addConstraint(int[] i,
                             double[] a,
                             int t,
                             double b)
```
    Adds a new constraint of the specified type to the problem. The two array arguments must be the same length, as their elements correspond to each other. Variables whose coefficients are zero need not be mentioned. Variables that are mentioned must have previously been added via addBooleanVariable(double) or addDiscreteVariable(double[]). The resulting constraint has the form:
    x_i * a ?= b
    where x_i represents the inference variables whose indexes are contained in the array i, * represents dot product, and ?= stands for the type of the constraint.
    This method is called by the other constraint adding methods in this class. It sorts the variables and their coefficients so that the presence of a given variable can be determined with IVector2D.binarySearch(int,int).
    
    Parameters:
    
    i - The indexes of the variables with non-zero coefficients.
    
    a - The coefficients of the variables with the given indexes.
    
    t - The type of comparison in this constraint.
    
    b - The new constraint will enforce equality with this constant.
  - addEqualityConstraint
```
public void addEqualityConstraint(int[] i,
                                  double[] a,
                                  double b)
```
    Adds a new fixed constraint to the problem. The two array arguments must be the same length, as their elements correspond to each other. Variables whose coefficients are zero need not be mentioned. Variables that are mentioned must have previously been added via addBooleanVariable(double) or addDiscreteVariable(double[]). The resulting constraint has the form:
    x_i * a = b
    where x_i represents the inference variables whose indexes are contained in the array i and * represents dot product.
    
    Parameters:
    
    i - The indexes of the variables with non-zero coefficients.
    
    a - The coefficients of the variables with the given indexes.
    
    b - The new constraint will enforce equality with this constant.
  - addGreaterThanConstraint
```
public void addGreaterThanConstraint(int[] i,
                                     double[] a,
                                     double b)
```
    Adds a new lower bounded constraint to the problem. The two array arguments must be the same length, as their elements correspond to each other. Variables whose coefficients are zero need not be mentioned. Variables that are mentioned must have previously been added via addBooleanVariable(double) or addDiscreteVariable(double[]). The resulting constraint has the form:
    x_i * a >= b
    where x_i represents the inference variables whose indexes are contained in the array i and * represents dot product.
    
    Parameters:
    
    i - The indexes of the variables with non-zero coefficients.
    
    a - The coefficients of the variables with the given indexes.
    
    b - The lower bound for the new constraint.
  - addLessThanConstraint
```
public void addLessThanConstraint(int[] i,
                                  double[] a,
                                  double b)
```
    Adds a new upper bounded constraint to the problem. The two array arguments must be the same length, as their elements correspond to each other. Variables whose coefficients are zero need not be mentioned. Variables that are mentioned must have previously been added via addBooleanVariable(double) or addDiscreteVariable(double[]). The resulting constraint has the form:
    x_i * a <= b
    where x_i represents the inference variables whose indexes are contained in the array i and * represents dot product.
    
    Parameters:
    
    i - The indexes of the variables with non-zero coefficients.
    
    a - The coefficients of the variables with the given indexes.
    
    b - The upper bound for the new constraint.
  - evaluate
```
public double evaluate(int[] x)
```
    This method evaluates the objective function on a potential (not necessarily feasible) solution.
    
    Parameters:
    
    x - The current settings of the inference variables.
    
    Returns:
    
    The value of the objective function with these variable settings.
  - write
```
public void write(StringBuffer buffer)
```
    Creates a textual representation of the ILP problem in an algebraic notation.
    
    Parameters:
    
    buffer - The created textual representation will be appended here.
  - toString
```
public String toString()
```
    Returns the representation created by write(StringBuffer).
    
    Overrides:
    
    toString in class Object

Class ZeroOneILPProblem

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

EQUALITY

LESS_THAN

GREATER_THAN

boundTypeSymbols

TOLERANCE

maximize

objectiveCoefficients

Av

Ac

boundTypes

bounds

Constructor Detail

ZeroOneILPProblem

ZeroOneILPProblem

Method Detail

reset

setMaximize

getMaximize

rows

columns

setObjectiveCoefficient

getObjectiveCoefficient

setConstraintCoefficient

getConstraintCoefficient

setBoundType

getBoundType

setConstraintBound

getConstraintBound

constraintsSatisfied

addBooleanVariable

addDiscreteVariable

addDiscreteVariable

addConstraint

addConstraint

addEqualityConstraint

addGreaterThanConstraint

addLessThanConstraint

evaluate

write

toString