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Multiobjective optimization of the inspection intervals of a nuclear safety system: A clustering-based framework for reducing the Pareto Front

Abstract : In this paper, a framework is developed for identifying a limited number of representative solutions of a multiobjective optimization problem concerning the inspection intervals of the components of a safety system of a nuclear power plant. Pareto Front solutions are first clustered into "families", which are then synthetically represented by a "head of the family" solution. Three clustering methods are analyzed. Level Diagrams are then used to represent, analyse and interpret the Pareto Fronts reduced to their head-of-the-family solutions. Two decision situations are considered: without or with decision maker preferences, the latter implying the introduction of a scoring system to rank the solutions with respect to the different objectives: a fuzzy preference assignment is then employed to this purpose. The results of the application of the framework of analysis to the problem of optimizing the inspection intervals of a nuclear power plant safety system show that the clustering-based reduction maintains the Pareto Front shape and relevant characteristics, while making it easier for the decision maker to select the final solution
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https://hal-supelec.archives-ouvertes.fr/hal-00610476
Contributor : Yanfu Li <>
Submitted on : Friday, July 22, 2011 - 10:26:28 AM
Last modification on : Wednesday, July 15, 2020 - 10:36:09 AM

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  • HAL Id : hal-00610476, version 1

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Enrico Zio, R. Bazzo. Multiobjective optimization of the inspection intervals of a nuclear safety system: A clustering-based framework for reducing the Pareto Front. Annals of Nuclear Energy, Elsevier Masson, 2010, 37 (6), pp.798-812. ⟨hal-00610476⟩

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