Hybrid Approach for Airspace Sectorization Based on K-Means Clustering and Genetic Algorithm Optimization

This paper presents a genetic optimization approach for airspace sectorization that combines K-means clustering and a genetic algorithm (GA). The algorithm minimizes the operating costs related to airspace complexities, unbalanced workloads, and inter-sector coordination requirements while respectin...

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Bibliographic Details

Published in:	2024 International Conference of the African Federation of Operational Research Societies (AFROS) pp. 1 - 5
Main Authors:	Addala, Manel, Mogtit, Abdessamed, Lagha, Mohand
Format:	Conference Proceeding
Language:	English
Published:	IEEE 03.11.2024
Subjects:	airspace sectorization balanced workload Clustering algorithms Complexity theory Costs genetic algorithm Genetic algorithms Genetics kmeans clustering algorithm Optimization Reliability Reproducibility of results Shape Stability analysis
Online Access:	Get full text
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