semvec/pypi-packages huggingface dataset:
aco 0.2.3
Ant Colony Optimization in Python
License: MIT
Requires Python: >=3.10,<4.0

# Ant Colony Optimization

##### Implementation of the Ant Colony Optimization algorithm in Python

> Currently works on 2D Cartesian coordinate system

## Installation

#### From PyPi

```shell
pip install aco
```

#### Using [Poetry](https://python-poetry.org/)

```shell
poetry add aco
```

## Usage

```python
AntColony(
    nodes,
    start=None,
    ant_count=300,
    alpha=0.5,
    beta=1.2,
    pheromone_evaporation_rate=0.40,
    pheromone_constant=1000.0,
    iterations=300,
)
```

### Travelling Salesman Problem
```python
import matplotlib.pyplot as plt
import random

from aco import AntColony


plt.style.use("dark_background")


COORDS = (
    (20, 52),
    (43, 50),
    (20, 84),
    (70, 65),
    (29, 90),
    (87, 83),
    (73, 23),
)


def random_coord():
    r = random.randint(0, len(COORDS))
    return r


def plot_nodes(w=12, h=8):
    for x, y in COORDS:
        plt.plot(x, y, "g.", markersize=15)
    plt.axis("off")
    fig = plt.gcf()
    fig.set_size_inches([w, h])


def plot_all_edges():
    paths = ((a, b) for a in COORDS for b in COORDS)

    for a, b in paths:
        plt.plot((a[0], b[0]), (a[1], b[1]))


plot_nodes()

colony = AntColony(COORDS, ant_count=300, iterations=300)

optimal_nodes = colony.get_path()

for i in range(len(optimal_nodes) - 1):
    plt.plot(
        (optimal_nodes[i][0], optimal_nodes[i + 1][0]),
        (optimal_nodes[i][1], optimal_nodes[i + 1][1]),
    )


plt.show()
```

![screenshot](screenshot.jpg)

---

#### Reference

- [Wikipedia](https://en.wikipedia.org/wiki/Ant_colony_optimization_algorithms)

- [pjmattingly/ant-colony-optimization](https://github.com/pjmattingly/ant-colony-optimization)