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Simulation-based algorithms for the optimization of sensor deployment

Abstract : Two simulation-based algorithms are presented, that have been successfully applied to an industrial optimization problem. These two algorithms have different and complementary features. One is fast, and sequential: it proceeds by running a population of targets and by dropping and activating a new sensor (or re-activating a sensor already available) where and when this action seems appropriate. The other is slow, iterative, and non-sequential: it proceeds by updating a population of deployment plans with guaranteed and increasing criterion value at each iteration, and for each given deployment plan, there is a population of targets running to evaluate the criterion. Finally, the two algorithms can cooperate in many different ways, to try and get the best of both approaches. A simple and efficient way is to use the deployment plans provided by the sequential algorithm as the initial population for the iterative algorithm.
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Contributor : Francois Le Gland Connect in order to contact the contributor
Submitted on : Tuesday, August 11, 2015 - 12:54:06 PM
Last modification on : Tuesday, June 14, 2022 - 9:19:45 AM



Yannick Kenné, François Le Gland, Christian Musso, Sébastien Paris, Yannick Glemarec, et al.. Simulation-based algorithms for the optimization of sensor deployment. Hoai An Le Thi; Tao Pham Dinh; Ngoc Thanh Nguyen. Proceedings of the 3rd International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences, Metz 2015, 360, Springer, pp.261-272, 2015, Advances in Intelligent Systems and Computing, 978-3-319-18166-0. ⟨10.1007/978-3-319-18167-7_23⟩. ⟨hal-01183819⟩



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