• Title/Summary/Keyword: Fuzzy Preference Scoring

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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.;Bazzo, R.
    • Nuclear Engineering and Technology
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    • v.42 no.4
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    • pp.414-425
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    • 2010
  • 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.

Optimal Selection of Energy System Design Using Fuzzy Framework (모호집합론을 사용한 에너지계통 설계의 최적선택)

  • 김성호;문주현
    • Proceedings of the Korea Society for Energy Engineering kosee Conference
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    • 1998.10a
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    • pp.3-8
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    • 1998
  • The present work proposes the potential fuzzy framework, based on fuzzy set theory, for supporting decision-making problems, especially, selection problems of a best design in the area of nuclear energy system. The framework proposed is composed of the hierarchical structure module, the assignment module, the fuzzification module, and the defuzzification module. In the structure module, the relationship among decision objectives, decision criteria, decision sub-criteria, and decision alternatives is hierarchically structured. In the assignment module, linguistic or rank scoring approach can be used to assign subjective and/or vague values to the decision analyst's judgment on decision variables. In the fuzzification module, fuzzy numbers are assigned to these values of decision variables. Using fuzzy arithmetic operations, for each alternative, fuzzy preference index as a fuzzy synthesis measure is obtained. In the defuzzification module, using one of methods ranking fuzzy numbers, these indices are defuzzified to overall utility values as a cardinality measure determining final scores. According these values, alternatives of interest are ranked and an optimal alternative is chosen. To illustrate the applicability of the framework proposed to selection problem, as a case example, the best option choice of four design options under five decision criteria for primary containment wall thickening around large penetrations in an advanced nuclear energy system is studied.

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