Abstract
While there is a variety of approaches and algorithms for optimizing the mission of a sensor, there are much less works which deal with the implementation of several sensors within a human organization. In this case, the management of the sensors is done through at least one human decision layer, and the sensors management as a whole arises as a bi-level optimization process. The following hypotheses are considered as realistic: Sensor handlers of first level plans their sensors by means of elaborated algorithmic tools based on accurate modelling of the environment; Higher level plans the handled sensors according to a global observation mission and on the basis of an approximated model of the environment and submit its plan to a costly assessment by the first level. This problem is related to the domain of experiment design. A generalization of the Efficient Global Optimization method (Jones, Schonlau and Welch) is proposed, based on a rare event simulation approach.
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Dambreville, F. (2014). Bi-level Sensor Planning Optimization Process with Calls to Costly Sub-processes. In: Nguyen, N.T., Attachoo, B., Trawiński, B., Somboonviwat, K. (eds) Intelligent Information and Database Systems. ACIIDS 2014. Lecture Notes in Computer Science(), vol 8398. Springer, Cham. https://doi.org/10.1007/978-3-319-05458-2_40
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DOI: https://doi.org/10.1007/978-3-319-05458-2_40
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