معرفی شرکت ها
aco-routing-1.0.4
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشترتوضیحات
A Python package to find the shortest path in a graph using Ant Colony Optimization (ACO).
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | aco-routing-1.0.4 |
| نام | aco-routing |
| نسخه کتابخانه | 1.0.4 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Hasnain Roopawalla |
| ایمیل نویسنده | hasnain.roopawalla@gmail.com |
| آدرس صفحه اصلی | https://github.com/hasnainroopawalla/ant-colony-optimization |
| آدرس اینترنتی | https://pypi.org/project/aco-routing/ |
| مجوز | MIT |
<h1 align="center">Ant Colony Optimization</h1>
[](https://github.com/hasnainroopawalla/Ant-Colony-Optimization/actions/workflows/develop.yml)
[](https://github.com/hasnainroopawalla/Ant-Colony-Optimization/actions/workflows/deploy.yml)
[](https://pypi.python.org/pypi/aco_routing/)
[](https://img.shields.io/pypi/pyversions/aco_routing.svg?style=plastic)
A Python package to find the shortest path in a graph using Ant Colony Optimization (ACO).
The Ant colony Optimization algorithm is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs ([source](https://en.wikipedia.org/wiki/Ant_colony_optimization_algorithms)).
## 📝 Table of Contents
- [Getting Started](#getting_started)
- [Usage](#usage)
- [Contents](#contents)
## 🏁 Getting Started <a name = "getting_started"></a>
### To install the package directly from PyPi:
```
$ pip install aco_routing
```
## 🎈 Usage <a name="usage"></a>
> **_Check out:_** [aco_routing/example.py](https://github.com/hasnainroopawalla/Ant-Colony-Optimization/tree/master/aco_routing/example.py)
Import all the dependencies.
```python
from aco_routing.utils.graph import Graph
from aco_routing.dijkstra import Dijkstra
from aco_routing.utils.simulator import Simulator
from aco_routing.aco import ACO
```
Create a `Graph` object.
```python
graph = Graph()
```
Create `Edges` between `Nodes` (nodes are implicitly created if they don't exist).
```python
graph.add_edge("A", "B", travel_time=2)
graph.add_edge("B", "C", travel_time=2)
graph.add_edge("A", "H", travel_time=2)
graph.add_edge("H", "G", travel_time=2)
graph.add_edge("C", "F", travel_time=1)
graph.add_edge("F", "G", travel_time=1)
graph.add_edge("G", "F", travel_time=1)
graph.add_edge("F", "C", travel_time=1)
graph.add_edge("C", "D", travel_time=10)
graph.add_edge("E", "D", travel_time=2)
graph.add_edge("G", "E", travel_time=2)
```
Define a `source` and `destination` as well create objects for the `Dijkstra` and `ACO` classes.
```python
source = "A"
destination = "D"
aco = ACO(graph)
dijkstra = Dijkstra(graph)
```
Find the shortest path between the `source` and `destination` as well the cost of the path using `Dijkstra` and `ACO`.
```python
dijkstra_path, dijkstra_cost = dijkstra.find_shortest_path(source, destination)
aco_path, aco_cost = aco.find_shortest_path(source, destination)
print(f"ACO - path: {aco_path}, cost: {aco_cost}")
print(f"Dijkstra - path: {dijkstra_path}, cost: {dijkstra_cost}")
```
Simulate a real-life scenario with various episodes of stochastically updating traffic conditions in a city.
```python
Simulator(graph).simulate(source, destination, num_episodes=100, plot=True)
```
## 📦 Contents <a name = "contents"></a>
### Graph
`aco_routing.utils.graph.Graph`
- A Directed Graph class which consists of `Nodes` and `Edges`.
- The `evaporation_rate` is initialized here.
### Node
`aco_routing.utils.graph.Node`
- A `Node` class which represents a node in the Graph and consists of various outgoing edges.
### Edge
`aco_routing.utils.graph.Edge`
- An `Edge` class which represents a link between 2 nodes in the Graph.
- Each `Edge` has 2 parameters:
- `travel_time`: The amount of time it takes to traverse the edge. A high value indicates more traffic.
- `pheromones`: A heuristic parameter i.e., the pheromone values deposited by the ants.
### Dijkstra
`aco_routing.dijkstra.Dijkstra`
- The baseline algorithm to compare the results of the candidate algorithm with.
- The Dijkstra's algorithm ([source](https://en.wikipedia.org/wiki/Dijkstra%27s_algorithm)) returns the shortest path between any 2 nodes in a graph.
### Ant
`aco_routing.utils.ant.Ant`
- The `Ant` class representing an ant that traverses the graph.
### ACO
`aco_routing.aco.ACO`
- The traditional Ant Colony Optimization algorithm that spawns various ants at random nodes and tries to find the shortest path between the specified source and destination.
### Simulator
`aco_routing.utils.simulator.Simulator`
- The simulator class is used to simulate and evaluate the performance of the candidate algorithm (ACO) with a baseline Dijkstra's Algorithm.
- It simulates a real-life city, where the traffic conditions change every episode in a conditionally stochastic manner.
- The ants continue to find the shortest path even after the traffic conditions change.
<hr>
## Contributing
- Post any issues and suggestions on the GitHub [issues](https://github.com/hasnainroopawalla/Ant-Colony-Optimization/issues) page.
- To contribute, fork the project and then create a pull request back to master.
## License
This project is licensed under the MIT License - see the [LICENSE](https://github.com/hasnainroopawalla/Ant-Colony-Optimization/blob/73b65a6fd14e3e5517b479cfecac1140f0ae7899/LICENSE) file for details.
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.6 | Python |
نحوه نصب
نصب پکیج whl aco-routing-1.0.4:
pip install aco-routing-1.0.4.whl
نصب پکیج tar.gz aco-routing-1.0.4:
pip install aco-routing-1.0.4.tar.gz