Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
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OPTIMIZATION OF THE TEST INTERVALS OF A NUCLEAR SAFETY SYSTEM BY GENETIC ALGORITHMS, SOLUTION CLUSTERING AND FUZZY PREFERENCE ASSIGNMENT

  • Zio, E. (Ecole Centrale Paris- Supelec Chair Systems Science and Energetic Challenge European Foundation for New Energy - EDF) ;
  • Bazzo, R. (Politecnico di Milano)
  • Received : 2009.12.11
  • Accepted : 2010.05.06
  • Published : 2010.08.31
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Abstract

In this paper, a procedure is developed for identifying a number of representative solutions manageable for decision-making in a multiobjective optimization problem concerning the test intervals of the components of a safety system of a nuclear power plant. Pareto Front solutions are identified by a genetic algorithm and then clustered by subtractive clustering into "families". On the basis of the decision maker's preferences, each family is then synthetically represented by a "head of the family" solution. This is done by introducing a scoring system that ranks the solutions with respect to the different objectives: a fuzzy preference assignment is employed to this purpose. Level Diagrams are then used to represent, analyze and interpret the Pareto Fronts reduced to the head-of-the-family solutions.

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References

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