https://github.com/ryomendev/uav-resourceallocation-major-project

The UAV Resource Allocation project uses Particle Swarm Optimization (PSO) to efficiently assign UAVs for delivering essential resources like medicine, food, and weapons to multiple outposts while minimizing energy consumption and ensuring high-priority deliveries. Optimized for real-world UAV logistics. 🚀
https://github.com/ryomendev/uav-resourceallocation-major-project

particle-swarm-optimization pso-algorithm swarm swarm-cluster

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The UAV Resource Allocation project uses Particle Swarm Optimization (PSO) to efficiently assign UAVs for delivering essential resources like medicine, food, and weapons to multiple outposts while minimizing energy consumption and ensuring high-priority deliveries. Optimized for real-world UAV logistics. 🚀

• Host: GitHub
• URL: https://github.com/ryomendev/uav-resourceallocation-major-project
• Owner: RyomenDev
• License: apache-2.0
• Created: 2025-03-06T02:40:25.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-03-14T03:56:56.000Z (about 1 year ago)
• Last Synced: 2025-03-14T04:29:35.197Z (about 1 year ago)
• Topics: particle-swarm-optimization, pso-algorithm, swarm, swarm-cluster
• Language: C++
• Homepage:
• Size: 26.9 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          

# UAV Resource Allocation using Particle Swarm Optimization (PSO)

## Overview

This project implements the **Particle Swarm Optimization (PSO)** algorithm for **UAV (Unmanned Aerial Vehicle) resource allocation**. The goal is to efficiently allocate UAVs to deliver essential resources such as **medicine, food, and weapons** to outposts while minimizing energy consumption and ensuring high-priority deliveries.

## Features

✅ **Takes input for:**

- **n**: Number of outposts

- **m**: Number of UAVs

- **UAV details**: Weight capacity, energy/km, total energy

- **Outpost details**: Resource needs (medicine, food, weapons), coordinates (x, y)

- **Base station coordinates**

✅ **Uses PSO to optimize assignments:**

- Minimizes energy consumption

- Prioritizes urgent resource deliveries

- Allocates UAVs based on travel distance and energy constraints

## How it Works

1. **Input Processing**: Reads the number of UAVs, outposts, and their respective details.

2. **Initialization**: Generates an initial swarm of potential UAV allocation solutions.

3. **Particle Movement**: Iteratively updates solutions based on velocity, local best, and global best solutions.

4. **Fitness Evaluation**: Computes energy consumption and ensures UAVs meet resource constraints.

5. **Convergence**: Continues optimization until an optimal or near-optimal allocation is found.

## Installation & Usage

### **Prerequisites**

- C++ Compiler (GCC, Clang, or MSVC)

- C++ Standard Library

### **Compilation & Execution**

```bash

 g++ -o uav_allocation main.cpp -std=c++17

 ./uav_allocation

```

## Applications

🚀 **Disaster Response** – Optimally deploy UAVs to deliver medical aid and supplies

🚀 **Military Operations** – Efficiently allocate UAVs for supply distribution in remote areas

🚀 **Logistics & Supply Chain** – Automating resource delivery using UAV fleets

## Future Possible Improvements

- 🔹 Incorporate **multi-objective optimization** (e.g., delivery time, fuel efficiency)

- 🔹 Implement **hybrid metaheuristic algorithms** (e.g., Genetic Algorithm + PSO)

- 🔹 Extend to **real-time dynamic allocation** with changing outpost demands

- 🔹 UAV **recharge stations** 

- 🔹 **multi-stop deliveries**

## License

This project is open-source under the **MIT License**.

## Contributors

- **Akash Mishra** (Developer & Researcher)

- **Biranjay Kumar Gupta** (Developer & Researcher)

- **Sunny Kumar** (Developer & Researcher)

For queries, reach out via GitHub or email.

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🚀 **Optimizing UAV resource allocation using AI-driven heuristics!** 🚀