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Multi-objective Optimization for Selecting and Scheduling Observations by Agile Earth Observing Satellites

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7492)

Abstract

This paper presents a biased random-key genetic algorithm for solving a multi-objective optimization problem concerning the management of agile Earth observing satellites. It addresses the selection and scheduling of a subset of photographs from a set of candidates in order to optimize two objectives: maximizing the total profit, and ensuring fairness among users by minimizing the maximum profit difference between users. Two methods, one based on dominance, the other based on indicator, are compared to select the preferred solutions. The methods are evaluated on realistic instances derived from the 2003 ROADEF challenge.

Keywords

  • Multi-objective optimization
  • Earth observing satellite
  • scheduling
  • genetic algorithm

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References

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© 2012 Springer-Verlag Berlin Heidelberg

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Tangpattanakul, P., Jozefowiez, N., Lopez, P. (2012). Multi-objective Optimization for Selecting and Scheduling Observations by Agile Earth Observing Satellites. In: Coello, C.A.C., Cutello, V., Deb, K., Forrest, S., Nicosia, G., Pavone, M. (eds) Parallel Problem Solving from Nature - PPSN XII. PPSN 2012. Lecture Notes in Computer Science, vol 7492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32964-7_12

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  • DOI: https://doi.org/10.1007/978-3-642-32964-7_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32963-0

  • Online ISBN: 978-3-642-32964-7

  • eBook Packages: Computer ScienceComputer Science (R0)