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Source: lp-solve
Section: math
Priority: optional
Maintainer: Juan Esteban Monsalve Tobon <esteban@v7w.com>
Uploaders: Rene Engelhard <rene@debian.org>, Anibal Monsalve Salazar <anibal@debian.org>
Build-Depends: debhelper (>= 9), libsuitesparse-dev (>= 1:3.4.0)
Standards-Version: 4.5.0
Homepage: http://lpsolve.sourceforge.net
Package: lp-solve
Architecture: any
Depends: ${shlibs:Depends}, ${misc:Depends}
Description: Solve (mixed integer) linear programming problems
The linear programming (LP) problem can be formulated as: Solve A.x >=
V1, with V2.x maximal. A is a matrix, x is a vector of (nonnegative)
variables, V1 is a vector called the right hand side, and V2 is a vector
specifying the objective function.
.
An integer linear programming (ILP) problem is an LP with the
constraint that all the variables are integers. In a mixed integer
linear programming (MILP) problem, some of the variables are integer
and others are real.
.
The program lp_solve solves LP, ILP, and MILP problems. It is slightly
more general than suggested above, in that every row of A (specifying
one constraint) can have its own (in)equality, <=, >= or =. The result
specifies values for all variables.
.
lp_solve uses the 'Simplex' algorithm and sparse matrix methods for
pure LP problems. If one or more of the variables is declared
integer, the Simplex algorithm is iterated with a branch and bound
algorithm, until the desired optimal solution is found. lp_solve can
read MPS format input files.
Package: lp-solve-doc
Section: doc
Architecture: all
Depends: ${misc:Depends}
Recommends: www-browser
Description: Solve (mixed integer) linear programming problems - documentation
The linear programming (LP) problem can be formulated as: Solve A.x >=
V1, with V2.x maximal. A is a matrix, x is a vector of (nonnegative)
variables, V1 is a vector called the right hand side, and V2 is a vector
specifying the objective function.
.
An integer linear programming (ILP) problem is an LP with the
constraint that all the variables are integers. In a mixed integer
linear programming (MILP) problem, some of the variables are integer
and others are real.
.
The program lp_solve solves LP, ILP, and MILP problems. It is slightly
more general than suggested above, in that every row of A (specifying
one constraint) can have its own (in)equality, <=, >= or =. The result
specifies values for all variables.
.
lp_solve uses the 'Simplex' algorithm and sparse matrix methods for
pure LP problems. If one or more of the variables is declared
integer, the Simplex algorithm is iterated with a branch and bound
algorithm, until the desired optimal solution is found. lp_solve can
read MPS format input files.
.
This package contains the documentation for the lp_solve program and
the library.
Package: liblpsolve55-dev
Section: libdevel
Architecture: any
Depends: libsuitesparse-dev, ${misc:Depends}
Description: Solve (mixed integer) linear programming problems - library
The linear programming (LP) problem can be formulated as: Solve A.x >=
V1, with V2.x maximal. A is a matrix, x is a vector of (nonnegative)
variables, V1 is a vector called the right hand side, and V2 is a vector
specifying the objective function.
.
An integer linear programming (ILP) problem is an LP with the
constraint that all the variables are integers. In a mixed integer
linear programming (MILP) problem, some of the variables are integer
and others are real.
.
The program lp_solve solves LP, ILP, and MILP problems. It is slightly
more general than suggested above, in that every row of A (specifying
one constraint) can have its own (in)equality, <=, >= or =. The result
specifies values for all variables.
.
lp_solve uses the 'Simplex' algorithm and sparse matrix methods for
pure LP problems. If one or more of the variables is declared
integer, the Simplex algorithm is iterated with a branch and bound
algorithm, until the desired optimal solution is found. lp_solve can
read MPS format input files.
.
This package contains the static library for developing programs using
liblpsolve.
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