• 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