Skip to main content

Python optimization library for mathematical programming.

## Project description

Python optimization library for mathematical programming.   ## Introduction

Pytimize is a python library for

• Formulating and solving complex linear, integer, and nonlinear programs.
• Performing combinatorial optimization with directed/undirected graphs and flows.
• Visualizing polyhedrons and displaying computation process.

Install using `pip install pytimize`!

Coming soon!

## Example

The following shows a code snippet for constructing a linear program and solving it with two phase simplex. For more detailed examples, please see `pytimize/examples`.

```>>> from pytimize.formulations.linear import variables, minimize
>>> a, b, c, d, e = variables(5)
>>> p = minimize(4*c - 11*d - e + 17).subject_to(
a + 2*c + 7*d <= 2 + e,
b - 4*c - 5*d >= 1 - 3*e
).where(
a >= 0,
b >= 0,
c >= 0,
d <= 0,
e <= 0
)
>>> p
Min [0. 0. 4. -11. -1.]x + 17.
Subject To:

[1.  0.   2.   7.  -1.]     ≤   [2.]
[0.  1.  -4.  -5.   3.]x    ≥   [1.]
x₄, x₅ ≤ 0
x₁, x₂, x₃ ≥ 0

>>> p.dual()
Max [2. 1.]x
Subject To:

[ 1.   0.]     ≤   [  0.]
[ 0.   1.]     ≤   [  0.]
[ 2.  -4.]x    ≤   [  4.]
[ 7.  -5.]     ≥   [-11.]
[-1.   3.]     ≥   [ -1.]
x₁ ≤ 0
x₂ ≥ 0

>>> p.to_sef(in_place=True)
Max [0. 0. -4. -11. -1. 0. 0.]x + 17.
Subject To:

[1.  0.   2.  -7.   1.  1.   0.]     =   [2.]
[0.  1.  -4.   5.  -3.  0.  -1.]x    =   [1.]
x ≥ 0

>>> solution, optimal_basis, certificate = p.two_phase_simplex()
>>> solution, optimal_basis, certificate
(array([2., 1., 0., 0., 0., 0., 0.]), [1, 2], array([0., 0.])
>>> p.verify_optimality(certificate)
True
>>> p.optimal_value()
17.0
```

You can also formulate the exact same program by specifying the objective function and constraints in matrix form:

```>>> from pytimize.programs import LinearProgram
>>> import numpy as np
>>> A = np.array([
[1, 0, 2, 7, -1],
[0, 1, -4, -5, 3]
])
>>> b = np.array([2, 1])
>>> c = np.array([0, 0, 4, -11, -1])
>>> z = 17
>>> p = LinearProgram(A, b, c, z, "min", ["<=", ">="], negative_variables=[4, 5])
>>> p
Min [0. 0. 4. -11. -1.]x + 17
Subject To:

[1.  0.   2.   7.  -1.]     ≤   [2.]
[0.  1.  -4.  -5.   3.]x    ≥   [1.]
x₄, x₅ ≤ 0
x₁, x₂, x₃ ≥ 0
```

## Contributing

Pytimize is a work in progress project. Contributions are welcome on a pull request basis.

## Credits

Pytimize is created and maintained by Terry Zheng, Jonathan Wang, and Colin He. Logo is designed by Kayla Estacio.

## Release history Release notifications | RSS feed

This version 0.0.2 0.0.1a0 pre-release

## Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for pytimize, version 0.0.2
Filename, size File type Python version Upload date Hashes
Filename, size pytimize-0.0.2.tar.gz (3.5 kB) File type Source Python version None Upload date Hashes