Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/72718
Title: Use of multiple objective evolutionary algorithms in optimizing surveillance requirements
Authors: Martorell, S.
Carlos, S.
Villanueva, J. F.
Sanchez, A. I.
Galvan, B. 
Salazar, D.
Cepin, M.
UNESCO Clasification: 1207 Investigación operativa
Keywords: Genetic algorithms
Multiobjective optimization
Technical specifications
Maintenance
Safety
Issue Date: 2006
Journal: Reliability Engineering and System Safety 
Abstract: This paper presents the development and application of a double-loop Multiple Objective Evolutionary Algorithm that uses a Multiple Objective Genetic Algorithm to perform the simultaneous optimization of periodic Test Intervals (TI) and Test Planning (TP). It takes into account the time-dependent effect of TP performed on stand-by safety-related equipment. TI and TP are part of the Surveillance Requirements within Technical Specifications at Nuclear Power Plants. It addresses the problem of multi-objective optimization in the space of dependable variables, i.e. TI and TP, using a novel flexible structure of the optimization algorithm. Lessons learnt from the cases of application of the methodology to optimize TI and TP for the High-Pressure Injection System are given. The results show that the double-loop Multiple Objective Evolutionary Algorithm is able to find the Pareto set of solutions that represents a. surface of non-dominated solutions that satisfy all the constraints imposed on the objective functions and decision variables. Decision makers can adopt then the best solution found depending on their particular preference, e.g. minimum cost, minimum unavailability.
URI: http://hdl.handle.net/10553/72718
ISSN: 0951-8320
DOI: 10.1016/j.ress.2005.11.038
Source: Reliability Engineering & System Safety [ISSN 0951-8320], v. 91 (9), p. 1027-1038, (Septiembre 2006)
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