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- W2020200523 abstract "The Particle Collision Algorithm (PCA) is a Metropolis-based algorithm loosely inspired by the physics of nuclear particle collision reactions, particularly scattering and absorption. This metaheuristic is applied to a Nuclear Power Plant Auxiliary Feedwater System surveillance tests policy optimization, and its performance is compared to previous results. The optimization problem consists in maximizing the system's average availability for a given period of time, considering realistic features such as (i) aging effects on standby components during the tests; (ii) revealing failures in the tests imply on corrective maintenance, increasing outage times; (iii) components have distinct test parameters (outage time, aging factors, etc.); (iv) tests are not necessarily periodic. The PCA outperforms the canonical genetic algorithm and two of its variants, ratifying the previous performance in another optimization problem." @default.
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- W2020200523 date "2008-01-01" @default.
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- W2020200523 title "A Metropolis Algorithm applied to a Nuclear Power Plant Auxiliary Feedwater System surveillance tests policy optimization" @default.
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- W2020200523 doi "https://doi.org/10.1016/j.pnucene.2007.09.004" @default.
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