Stochastic satellite tracking with constrained budget via structured-chromosome genetic algorithms
Gentile, Lorenzo and Greco, Cristian and Minisci, Edmondo and Bartz-Beielstein, Thomas and Vasile, Massimiliano (2021) Stochastic satellite tracking with constrained budget via structured-chromosome genetic algorithms. Optimization and Engineering, 24 (1). pp. 257-290. ISSN 1389-4420 (https://doi.org/10.1007/s11081-021-09693-1)
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Abstract
This paper focuses on the scheduling under uncertainty of satellite tracking from a heterogeneous network of ground stations taking into account allocated resources. An optimisation-based approach is employed to efficiently select the optimal tracking schedule that minimises the final estimation uncertainty. Specifically, the scheduling is formulated as a variable-size problem, and a Structured-Chromosome Genetic Algorithm is developed to tackle the mixed-discrete global optimisation. The search algorithm employs genetic operators specifically revised to handle hierarchical search spaces. An orbit determination routine is run within each call to the fitness function to quantify the estimation uncertainty resulting from each candidate tracking schedule. The developed scheduler is tested on the tracking optimisation of a satellite in low Earth orbit, a highly perturbed dynamical regime. The obtained results show that the variable-size variants of Genetic Algorithms always outperform the fixed-size counterparts employed for comparison. In particular, Structured-Chromosome Genetic Algorithm is shown to find significantly better schedules under severely limited budgets.
ORCID iDs
Gentile, Lorenzo, Greco, Cristian ORCID: https://orcid.org/0000-0001-5996-2114, Minisci, Edmondo ORCID: https://orcid.org/0000-0001-9951-8528, Bartz-Beielstein, Thomas and Vasile, Massimiliano ORCID: https://orcid.org/0000-0001-8302-6465;-
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Item type: Article ID code: 78621 Dates: DateEvent7 November 2021Published7 November 2021Published Online28 September 2021AcceptedSubjects: Technology > Mechanical engineering and machinery Department: Faculty of Engineering > Mechanical and Aerospace Engineering
Strategic Research Themes > Ocean, Air and Space
Strategic Research Themes > Measurement Science and Enabling Technologies
Technology and Innovation Centre > Advanced Engineering and ManufacturingDepositing user: Pure Administrator Date deposited: 17 Nov 2021 16:29 Last modified: 11 Nov 2024 13:17 URI: https://strathprints.strath.ac.uk/id/eprint/78621