ORDER_ASSIGNMENT_AND_PATH_OPTIMIZATION

📦 Project Description

ORDER_ASSIGNMENT_AND_PATH_OPTIMIZATION is a Python-based solution developed to optimize order assignments and delivery routes for logistics companies. The primary goal is to enhance operational efficiency and maximize profits by implementing advanced algorithms for order distribution and path optimization.

🧠 Overview

This project addresses the challenges faced by delivery companies in assigning orders to riders and determining the most efficient delivery routes. By leveraging optimization techniques, the system aims to reduce delivery times, balance rider workloads, and improve overall customer satisfaction.

📁 Project Structure

• Assignment.py: Contains functions related to assigning orders to riders.
• Optimize_route.py: Implements route optimization algorithms to determine the most efficient delivery paths.
• generate_matrix.py: Generates distance or cost matrices used in optimization calculations.
• nearby_order.py: Identifies orders that are geographically close to each other to facilitate batch deliveries.
• plot.py: Provides visualization tools for routes and assignments.
• using_buffer_scheduling.py: Main script that integrates order assignment and route optimization functionalities.
• utils.py: Contains utility functions used across various modules.
• rider.json: Sample data representing rider information.
• simulation.json: Sample data representing order simulations for testing purposes.
• test.py: Script for testing the functionalities of different modules.

🚀 Features

• Order Assignment: Efficiently assigns orders to available riders based on various constraints and optimization criteria.
• Route Optimization: Calculates the most efficient delivery routes to minimize travel time and distance.
• Visualization: Provides graphical representations of routes and assignments for better understanding and analysis.
• Scalability: Designed to handle a large number of orders and riders, making it suitable for real-world applications.

🛠️ Technologies Used

• Programming Language: Python
• Libraries:
  • NumPy
  • Matplotlib
  • Copy
  • Random

🧰 Installation

To set up the project locally, follow these steps:

1. Clone the Repository:

   git clone https://github.com/devjayswal/ORDER_ASSIGNMENT_AND_PATH_OPTIMIZATION.git

2. Navigate to the Project Directory:

   cd ORDER_ASSIGNMENT_AND_PATH_OPTIMIZATION

3. Install Dependencies:

   pip install -r requirements.txt

💡 Usage

1. Prepare Data:

   • Ensure that rider.json and simulation.json files are populated with appropriate data.

2. Run the Main Script:

   python using_buffer_scheduling.py

3. Visualize Results:

   • Use plot.py to generate visual representations of the optimized routes and assignments.

📊 Data Analysis

The project includes tools for analyzing the efficiency of order assignments and delivery routes. By examining the output visualizations and performance metrics, users can gain insights into operational improvements.

🤝 Contributing

Contributions are welcome! To contribute:

1. Fork the Repository
2. Create a New Branch:

   git checkout -b feature/YourFeature

3. Commit Your Changes:

   git commit -m "Add YourFeature"

4. Push to the Branch:

   git push origin feature/YourFeature

5. Open a Pull Request

Please ensure your code adheres to the project's coding standards and includes relevant tests.

📄 License

This project is licensed under the MIT License. See the LICENSE file for details.

📬 Contact

For any inquiries or feedback, please contact [email protected].