Splitting Method for Spatio-temporal Sensors Deployment in Underwater Systems

  • Mathieu Chouchane
  • Sébastien Paris
  • François Le Gland
  • Mustapha Ouladsine
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7245)


In this paper, we present a novel stochastic optimization algorithm based on the rare events simulation framework for sensors deployment in underwater systems. More precisely, we focus on finding the best spatio-temporal deployment of a set of sensors in order to maximize the detection probability of an intelligent and randomly moving target in an area under surveillance. Based on generalized splitting technique with a dedicated Gibbs sampler, our approach does not require any state-space discretization and rely on the evolutionary framework.


Evolutionary algorithm Stochastic optimization Generalized splitting Genetic algorithm Gibbs sampler 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Mathieu Chouchane
    • 1
  • Sébastien Paris
    • 1
  • François Le Gland
    • 2
  • Mustapha Ouladsine
    • 1
  1. 1.LSISAix-Marseille University, Domaine universitaire de Saint-JérômeMarseille Cedex 20France
  2. 2.INRIA RennesRennes CedexFrance

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