CITATION.cff

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cff-version: 1.2.0
title: >-
  Air Traffic Management Using a GPU-Accelerated Genetic
  Algorithm
message: 'If you use this software, please cite it as below.'
type: software
authors:
  - given-names: Rahul
    family-names: Rampure
    email: rahulrampure@hotmail.com
    affiliation: PES University
    orcid: 'https://orcid.org/0000-0003-0050-6442'
  - given-names: Raghav
    family-names: Tiruvallur
    email: rtiruvallur@gmail.com
    affiliation: PES University
  - given-names: Vybhav
    family-names: Acharya
    email: vybhavacharya@yahoo.com
    affiliation: PES University
  - given-names: Shashank
    family-names: Navad
    email: shashanknavad@gmail.com
    affiliation: PES University
  - given-names: Preethi
    family-names: P
    email: preethip@pes.edu
    affiliation: PES University
identifiers:
  - type: doi
    value: 10.2478/ttj-2023-0021
repository-code: >-
  https://github.com/CascadingRadium/Air-Traffic-Distribution
abstract: >-
  Air traffic management is becoming highly complex with the
  rapid increase in the number of commercial and cargo
  flights,leading to increased traffic congestion and flight
  delays. To mitigate these issues, we present a flight path
  generation system thatdistributes the aeroplanes across
  the airspace and imparts minimal delays to the flight if
  required, thus ensuring that the aircraft followsthe
  shortest route wherein it encounters the least amount of
  traffic. We develop a parallel genetic algorithm in CUDA-C
  with a novelfitness function allowing the system to reach
  an optimal solution where the air traffic density is
  minimised. The proposed algorithmwas tested on one day’s
  domestic flight schedule and achieved an 18% reduction in
  traffic density, with the flight times and delaysremaining
  proportional to the data observed in the existing air
  traffic management system.
keywords:
  - Genetic Algorithm
  - Air Traffic Management
  - CUDA
  - Spectral Clustering
license: MIT
commit: 7fea8f5
version: '5.0'
date-released: '2022-12-13'