Safety Systems Optimum Design by Multicriteria Evolutionary Algorithms

In this work new safety systems multiobjective optimum design methodologies are introduced and compared. Various multicriteria evolutionary algorithms are analysed (SPEA2, NSGAII and controlled elitist-NSGAII) and applied to a Containment Spray Injection System of a nuclear power plant. Influence of various mutation rates is considered. A double minimization is handled: unavailability and cost of the system. The comparative statistical results of the test case show a convergence study during evolution by means of certain metrics that measure front coverage and distance to the optimal front. Results succeed in solving the problem.