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
Link To Document :
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