# [PPL-devel] ppl/src LP_Problem.defs.hh

Sebastian Pop sebastian.pop at cri.ensmp.fr
Thu Sep 21 13:29:08 CEST 2006

Enea Zaffanella wrote:
> CVSROOT:	/cvs/ppl
> Module name:	ppl
> Changes by:	zaffanella at cs.unipr.it	2006-09-21 10:05:24
>
> Modified files:
> 	src            : LP_Problem.defs.hh
>
> Log message:
> 	Do not let the user assume that we solve the LP Problem by using a fixed
> 	algorithm (future releases may use a different one).
>

Fix some typos in that file.

Sebastian

Index: LP_Problem.defs.hh
===================================================================
RCS file: /cvs/ppl/ppl/src/LP_Problem.defs.hh,v
retrieving revision 1.21
diff -d -u -p -r1.21 LP_Problem.defs.hh
--- LP_Problem.defs.hh	21 Sep 2006 09:17:11 -0000	1.21
+++ LP_Problem.defs.hh	21 Sep 2006 11:26:16 -0000
@@ -56,7 +56,7 @@ operator<<(std::ostream& s, const LP_Pro
- the feasible region, by means of a finite set of linear equality
and non-strict inequality constraints;
- the objective function, described by a Linear_Expression;
-   - the oprimization mode (either maximization or minimization).
+   - the optimization mode (either maximization or minimization).

The class provides support for the (incremental) solution of the
LP problem based on the simplex method. The result of the resolution
@@ -81,7 +81,7 @@ public:
the origin of the vector space is an optimal solution.

\param dim
-    The dimension of the vector space encosing \p *this
+    The dimension of the vector space enclosing \p *this
(optional argument with default value \f$0\f$).

\exception std::length_error
@@ -177,7 +177,7 @@ private:
public:
/*! \brief
A type alias for the read-only iterator on the constraints
-    defining the feasible reagion.
+    defining the feasible region.
*/
typedef Constraint_Sequence::const_iterator const_iterator;

@@ -465,7 +465,7 @@ private:

\param unfeasible_tableau_rows
This will contain all the row indexes of the tableau that are no more
-    satisfied after adding more contraints to \p *this.
+    satisfied after adding more constraints to \p *this.

\param satisfied_ineqs
This will contain all the row indexes of the tableau that are already
@@ -486,7 +486,7 @@ private:

\return
The column index of the variable that enters the base. If no such
-    variable exists, optimality was achieved and <CODE>0</CODE> is retuned.
+    variable exists, optimality was achieved and <CODE>0</CODE> is returned.
*/
dimension_type textbook_entering_index() const;

@@ -538,7 +538,7 @@ private:

\return
The column index of the variable that enters the base. If no such
-    variable exists, optimality was achieved and <CODE>0</CODE> is retuned.
+    variable exists, optimality was achieved and <CODE>0</CODE> is returned.

To compute the entering_index, the steepest edge algorithm chooses
the index j' such that \f$\frac{d_{j}}{\|\Delta x^{j} \|}\f$ is the
@@ -551,7 +551,7 @@ private:
\f]
Recall that, due to the Integer implementation of the algorithm, our
tableau doesn't contain the real'' \f$\alpha\f$ values, but these
-    can be computed dividing the value of the cofficient by the value of
+    can be computed dividing the value of the coefficient by the value of
the variable in base. Obviously the result may not be an Integer, so
we will proceed in another way: the following code will compute the
lcm of all the variables in base to get the good weight'' of each
@@ -576,7 +576,7 @@ private:
dimension_type& row_index) const;

/*! \brief
-    Computes a valid generator that satisifies all the constraints of the
+    Computes a valid generator that satisfies all the constraints of the
Linear Programming problem associated to \p *this.
*/
void compute_generator() const;

`