- libc6 (>= 2.29)
- libcolamd2 (>= 1:4.5.2)

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.

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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.

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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.

Homepage Source Package

- libc6 (>= 2.29)
- libcolamd2 (>= 1:4.5.2)

**Installed Size**: 663.6 kB

**Architectures**: amd64 arm64