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

 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! 🚀