# SuanShu, a Java numerical and statistical library

com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.solution

## Class LPUnboundedMinimizer

• java.lang.Object
• com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.solution.LPUnboundedMinimizer
• ### Field Summary

Fields
Modifier and Type Field and Description
protected int lambdaCol
protected SimplexTable table
• ### Constructor Summary

Constructors
Constructor and Description
LPUnboundedMinimizer(SimplexTable table, int lambdaCol)
Construct the solution for an unbounded linear programming problem.
• ### Method Summary

All Methods
Modifier and Type Method and Description
SimplexTable getResultantTableau()
Get the solution simplex table as a result of solving a linear programming problem.
ImmutableVector minimizer()
This is the same as the u vector, such that the direction of arbitrarily negative can be computed by adjusting λ.
double minimum()
Get the (approximate) minimum found.
ImmutableVector v()
When the problem is unbounded, the direction of arbitrarily negative can be computed by adjusting λ.
• ### Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
• ### Field Detail

• #### table

protected final SimplexTable table
• #### lambdaCol

protected final int lambdaCol
• ### Constructor Detail

• #### LPUnboundedMinimizer

public LPUnboundedMinimizer(SimplexTable table,
int lambdaCol)
Construct the solution for an unbounded linear programming problem.
Parameters:
table - the table of the current (intermediate) solution of a linear programming problem
lambdaCol - the column index for which there is no row that passes the ratio test (hence the problem is unbounded); when the problem is bounded, lambdaCol = 0
• ### Method Detail

• #### getResultantTableau

public SimplexTable getResultantTableau()
Description copied from interface: LPSimplexMinimizer
Get the solution simplex table as a result of solving a linear programming problem.
Specified by:
getResultantTableau in interface LPSimplexMinimizer
Returns:
the solution simplex table as a result of solving a linear programming problem
• #### minimum

public double minimum()
Description copied from interface: MinimizationSolution
Get the (approximate) minimum found.
Specified by:
minimum in interface MinimizationSolution<Vector>
Returns:
the (approximate) minimum found
• #### minimizer

public ImmutableVector minimizer()
This is the same as the u vector, such that the direction of arbitrarily negative can be computed by adjusting λ.
u + λv
Specified by:
minimizer in interface MinimizationSolution<Vector>
Returns:
the u vector
• #### v

public ImmutableVector v()
When the problem is unbounded, the direction of arbitrarily negative can be computed by adjusting λ.
u + λv
where u = minimizer().

This is only meaningful in the case where the problem is unbounded.

Returns:
the v vector