Splitting method for spatio-temporal sensors deployment in underwater systems

Authors:
Mathieu Chouchane;Sébastien Paris;François Le Gland;Mustapha Ouladsine
Affiliations:
LSIS, Aix-Marseille University, Domaine universitaire de Saint-Jérôme, Marseille Cedex 20, France;LSIS, Aix-Marseille University, Domaine universitaire de Saint-Jérôme, Marseille Cedex 20, France;INRIA Rennes, Rennes Cedex, France;LSIS, Aix-Marseille University, Domaine universitaire de Saint-Jérôme, Marseille Cedex 20, France
Venue:
EvoCOP'12 Proceedings of the 12th European conference on Evolutionary Computation in Combinatorial Optimization
Year:
2012

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Abstract

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.