Table of Contents Author Guidelines Submit a Manuscript
Mobile Information Systems
Volume 8, Issue 4, Pages 351-377
http://dx.doi.org/10.3233/MIS-2012-00153

Genetic Algorithms for Satellite Scheduling Problems

Fatos Xhafa,1 Junzi Sun,2 Admir Barolli,3 Alexander Biberaj,4 and Leonard Barolli5

1Department of Languages and Informatics Systems, Technical University of Catalonia, Barcelona, Spain
2Centre de Tecnologia Aeroespacial, Barcelona, Spain
3Seikei University, Tokyo, Japan
4Polytechnic University of Tirana, Tirana, Albania
5Fukuoka Institute of Technology, Fukuoka, Japan

Received 12 November 2012; Accepted 12 November 2012

Copyright © 2012 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Recently there has been a growing interest in mission operations scheduling problem. The problem, in a variety of formulations, arises in management of satellite/space missions requiring efficient allocation of user requests to make possible the communication between operations teams and spacecraft systems. Not only large space agencies, such as ESA (European Space Agency) and NASA, but also smaller research institutions and universities can establish nowadays their satellite mission, and thus need intelligent systems to automate the allocation of ground station services to space missions. In this paper, we present some relevant formulations of the satellite scheduling viewed as a family of problems and identify various forms of optimization objectives. The main complexities, due highly constrained nature, windows accessibility and visibility, multi-objectives and conflicting objectives are examined. Then, we discuss the resolution of the problem through different heuristic methods. In particular, we focus on the version of ground station scheduling, for which we present computational results obtained with Genetic Algorithms using the STK simulation toolkit.