DocumentCode :
2829916
Title :
A Genetic Algorithm for Ground Station Scheduling
Author :
Sun, Junzi ; Xhafa, Fatos
Author_Institution :
Aerosp. Res. & Technol. Centre, CTAE, Barcelona, Spain
fYear :
2011
fDate :
June 30 2011-July 2 2011
Firstpage :
138
Lastpage :
145
Abstract :
In this paper we address the resolution of the Ground Station Scheduling problem by Genetic Algorithms. Ground Stations (GS) are required during spacecraft (S/C) operations to provide communications links between operations teams and the S/C systems. Basic communication types, such as telemetry, tele-command and tracking, are all supported by the same satellite and GS systems. The allocation of ground resources to S/C is a highly constrained problem and traditionally has been conducted manually: stations are selected for communication support with certain S/C for certain periods. The manual approach has clear limitations and new modern scheduling approaches are needed to tackle with the complexity of the problem and produce optimal solutions to scheduling operations. We propose the use of Genetic Algorithm, a well-known family of population-based methods, for solving the problem. A series of genetic operators have been designed to find the configuration that outputs the best GA solution for the problem. The proposed GA has been implemented in Matlab and experimentally studied on a set of randomly generated instances. The results of the study showed the effectiveness of the proposed GA algorithm.
Keywords :
genetic algorithms; scheduling; space vehicles; Matlab; genetic algorithm; ground station scheduling; population-based methods; spacecraft; Arrays; Biological cells; Encoding; Genetic algorithms; Schedules; Scheduling; Space vehicles; Constraint optimization; Genetic Algorithms; Ground Scheduling; Spacecraft operations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Complex, Intelligent and Software Intensive Systems (CISIS), 2011 International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-61284-709-2
Electronic_ISBN :
978-0-7695-4373-4
Type :
conf
DOI :
10.1109/CISIS.2011.29
Filename :
5988980
Link To Document :
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