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.
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Chouchane, M., Paris, S., Le Gland, F., Ouladsine, M. (2012). Splitting Method for Spatio-temporal Sensors Deployment in Underwater Systems. In: Hao, JK., Middendorf, M. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2012. Lecture Notes in Computer Science, vol 7245. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29124-1_21
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DOI: https://doi.org/10.1007/978-3-642-29124-1_21
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