DocumentCode
1927437
Title
A Struggle Genetic Algorithm for Ground Stations Scheduling Problem
Author
Xhafa, Fatos ; Herrero, Xavier ; Barolli, Admir ; Takizawa, Makoto
Author_Institution
Tech. Univ. of Catalonia, Barcelona, Spain
fYear
2012
fDate
19-21 Sept. 2012
Firstpage
70
Lastpage
76
Abstract
The Ground Station Scheduling is one of the most important problems in the field of Satellite-Scheduling. This problem consists in planning feasible planning of communications between satellites or spacecraft (SC) and operations teams of Ground Station (GS). The information received in these communications is usually basic information such as telemetry, tracking information or tasks to perform, so usually the time required for communication is usually quite smaller than the window of visibility. Typically, the assignment of the Ground Stations to Spacecraft is a very limited and small enough to make a manual planning, defined by short periods of time. However, resource allocation of a ground station on a mission has a high cost, and automation of this process provides many benefits not only in terms of management, but in economic terms as well. The problem is known for its high complexity and is an over-constrained problem. In this paper, we present the resolution of the problem through Struggle Genetic Algorithms. Struggle GA is a version of GAs that distinguishes for its efficiency in maintaining the diversity of the population through genetic evolution. We present some computational results for the case of the multi-ground stations scheduling obtained with Struggle GA using the STK simulation toolkit.
Keywords
genetic algorithms; planning; resource allocation; satellite telemetry; scheduling; space vehicles; STK simulation toolkit; economic terms; feasible planning; genetic evolution; multiground stations scheduling; over-constrained problem; resource allocation; satellite scheduling; spacecraft; struggle genetic algorithm; telemetry; tracking information; Genetic algorithms; Planning; Processor scheduling; Scheduling; Sociology; Space vehicles; Statistics; Constraint programming; Ground station scheduling; Satellite scheduling; Simulation; Struggle Genetic Algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Networking and Collaborative Systems (INCoS), 2012 4th International Conference on
Conference_Location
Bucharest
Print_ISBN
978-1-4673-2279-9
Type
conf
DOI
10.1109/iNCoS.2012.125
Filename
6337901
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