{"id":24569088,"url":"https://github.com/ryomendev/uav-resourceallocation-minor-project","last_synced_at":"2026-02-17T02:02:02.335Z","repository":{"id":263736803,"uuid":"873406518","full_name":"RyomenDev/UAV-resourceAllocation-minor-project","owner":"RyomenDev","description":"project models an Unmanned Aerial Vehicle (UAV) resource allocation system to optimize the delivery of essential resources (medicine, food, and weapons) to various outposts.","archived":false,"fork":false,"pushed_at":"2025-01-13T06:17:01.000Z","size":10953,"stargazers_count":2,"open_issues_count":1,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-07-06T10:06:58.554Z","etag":null,"topics":["algorithms","cpp","efficiency","oops","oops-in-cpp","resource-allocation","uav"],"latest_commit_sha":null,"homepage":"","language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/RyomenDev.png","metadata":{"files":{"readme":"readMe.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-10-16T05:45:15.000Z","updated_at":"2025-01-13T06:17:04.000Z","dependencies_parsed_at":null,"dependency_job_id":"d6ae9006-ab07-4630-939b-7219ea5df4da","html_url":"https://github.com/RyomenDev/UAV-resourceAllocation-minor-project","commit_stats":null,"previous_names":["ryomendev/minor-project","ryomendev/uav-resourceallocation-minor-project"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/RyomenDev/UAV-resourceAllocation-minor-project","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RyomenDev%2FUAV-resourceAllocation-minor-project","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RyomenDev%2FUAV-resourceAllocation-minor-project/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RyomenDev%2FUAV-resourceAllocation-minor-project/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RyomenDev%2FUAV-resourceAllocation-minor-project/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/RyomenDev","download_url":"https://codeload.github.com/RyomenDev/UAV-resourceAllocation-minor-project/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RyomenDev%2FUAV-resourceAllocation-minor-project/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29530133,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-17T00:57:22.232Z","status":"online","status_checked_at":"2026-02-17T02:00:08.105Z","response_time":100,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["algorithms","cpp","efficiency","oops","oops-in-cpp","resource-allocation","uav"],"created_at":"2025-01-23T14:56:14.366Z","updated_at":"2026-02-17T02:02:02.270Z","avatar_url":"https://github.com/RyomenDev.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Efficient Allocation of Unmanned Aerial Vehicles (UAVs)\n\n## Table of Contents\n1. [Introduction](#introduction)\n2. [Problem Definition](#problem-definition)\n3. [System Design and Implementation](#system-design-and-implementation)\n4. [Algorithmic Approach](#algorithmic-approach)\n   - [Graph Representation and Dijkstra’s Algorithm](#graph-representation-and-dijkstras-algorithm)\n   - [Priority Ordering](#priority-ordering)\n   - [UAV Selection and Allocation](#uav-selection-and-allocation)\n   - [Weight and Delivery Calculations](#weight-and-delivery-calculations)\n5. [Optimization and Results](#optimization-and-results)\n6. [Code Architecture](#code-architecture)\n7. [Future Enhancements](#future-enhancements)\n8. [Conclusion](#conclusion)\n\n---\n\n## Introduction\nEfficient allocation of UAVs is essential for scenarios where resources must be transported from a central base to multiple outposts with varying demands and deadlines. This system uses Object-Oriented Programming (OOP) principles and graph-based algorithms to optimize the allocation process.\n\n---\n\n## Problem Definition\nThe aim is to transport resources such as medicine, food, and weapons from a central base to multiple outposts efficiently. Challenges include:\n- Meeting varying demands and deadlines.\n- Minimizing delivery times.\n- Efficiently utilizing UAVs while adhering to constraints like weight, speed, and travel distance.\n\n---\n\n## System Design and Implementation\nThis project implements:\n- A graph representation for calculating optimal routes.\n- Priority-based delivery scheduling.\n- Capacity-based UAV allocation.\n\n---\n\n## Algorithmic Approach\n### Graph Representation and Dijkstra’s Algorithm\n- Represent the delivery area as a graph with nodes (locations) and edges (routes).\n- Use Dijkstra’s Algorithm to calculate the shortest path from the base to each outpost.\n\n### Priority Ordering\n- Prioritize deliveries based on deadlines, urgency, and demand.\n\n### UAV Selection and Allocation\n- Select UAVs based on capacity, speed, and distance constraints.\n- Allocate resources to maximize delivery efficiency.\n\n### Weight and Delivery Calculations\n- Ensure UAVs operate within weight and distance limits.\n- Handle partial deliveries if outpost demands exceed UAV capacity.\n\n---\n\n## Optimization and Results\n- Minimized delivery times.\n- Efficient UAV utilization.\n- Adherence to operational constraints.\n\n---\n\n## Code Architecture\n1. **Graph Class:**\n   - Represents locations and routes.\n   - Implements Dijkstra’s Algorithm.\n\n2. **UAV Class:**\n   - Encapsulates UAV properties like capacity, speed, and range.\n\n3. **DeliveryManager Class:**\n   - Manages resource allocation and scheduling.\n   - Prioritizes deliveries and allocates UAVs.\n\n4. **Main Program:**\n   - Coordinates the system.\n   - Reads input data and invokes classes for processing.\n\n---\n\n## Future Enhancements\n- Integration with real-time traffic and weather data.\n- Dynamic UAV reallocation for emergency deliveries.\n- Support for additional constraints like energy consumption.\n\n---\n\n## Conclusion\nThis system efficiently allocates UAVs to deliver resources to outposts while adhering to constraints. It minimizes delivery times, meets deadlines, and ensures optimal resource utilization.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fryomendev%2Fuav-resourceallocation-minor-project","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fryomendev%2Fuav-resourceallocation-minor-project","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fryomendev%2Fuav-resourceallocation-minor-project/lists"}