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https://github.com/iamrajhans/mcts
monte carlo tree search implementation in python
https://github.com/iamrajhans/mcts
google-maps monte-carlo-tree-search route-optimization
Last synced: 7 days ago
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monte carlo tree search implementation in python
- Host: GitHub
- URL: https://github.com/iamrajhans/mcts
- Owner: iamrajhans
- License: mit
- Created: 2025-01-13T09:20:10.000Z (26 days ago)
- Default Branch: main
- Last Pushed: 2025-01-13T09:31:09.000Z (26 days ago)
- Last Synced: 2025-01-13T10:35:04.192Z (26 days ago)
- Topics: google-maps, monte-carlo-tree-search, route-optimization
- Language: Python
- Homepage:
- Size: 6.84 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Logistics Route Optimization with Monte Carlo Tree Search
This project demonstrates how to optimize a delivery route using the **Monte Carlo Tree Search (MCTS)** algorithm, integrated with the **Google Maps API** for real-world distance calculations. The goal is to minimize delivery costs and time by finding the most efficient route.
---
## Features
- Utilizes **Monte Carlo Tree Search** for route optimization.
- Integrates **Google Maps API** for accurate distance and route calculations.
- Scalable to multiple destinations.
- Provides an optimal delivery route based on simulations and backpropagation.
---
## Prerequisites
### 1. Python Installation
Ensure you have Python 3.7 or higher installed. You can download it from [python.org](https://www.python.org/).
### 2. Required Libraries
Install the required Python libraries using pip:
```bash
pip install -r requirements.txt
```
### 3. Google Maps API Key
- Obtain a Google Maps API key from the [Google Cloud Console](https://console.cloud.google.com/).
- Enable the **Directions API** for your project.
- Replace the placeholder `YOUR_GOOGLE_MAPS_API_KEY` in the code with your actual API key.
---
## How to Run
### 1. Clone the Repository
```bash
git clone https://github.com/iamrajhans/mcts.git
cd mcts
```
### 2. Configure the API Key
Open the script file and update the following line with your Google Maps API key:
```python
gmaps = googlemaps.Client(key="GOOGLE_MAPS_API_KEY")
```
### 3. Run the Script
Execute the Python script:
```bash
python mcts.py
```
---
## Example
### Input:
- Starting Location: **Bangalore**
- Delivery Destinations:
- Kempegowda International Airport Bengaluru,
- Cubbon Park, Bangalore
### Output:
```
Optimal Route: Kempegowda International Airport Bengaluru -> Cubbon Park, Bangalore
```
---
## Project Structure
```
logistics-route-optimization/
├── mcts.py # Main Python script for MCTS and route optimization
├── README.md # Documentation file
└── requirements.txt # List of required Python libraries
```
---
## Concepts Used
### 1. Monte Carlo Tree Search (MCTS)
MCTS is a heuristic search algorithm that balances exploration and exploitation to optimize decision-making. It iteratively builds a decision tree by simulating possible outcomes and refining the tree.
### 2. Google Maps API
The Google Maps API is used to calculate distances between locations, providing real-world accuracy for route optimization.
---
## Limitations
- **API Quota**: The script is limited by the free tier quota of the Google Maps API.
- **Scalability**: Computational complexity increases with the number of destinations.
---
## Future Improvements
- Include **live traffic data** for real-time optimization.
- Allow dynamic updates (e.g., new destinations during route execution).
- Visualize the optimal route on a map.
---