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Basics of genetic algorithms optimization for RAMS applications
Authors:M. Marseguerra   E. Zio  S. Martorell
Affiliation:aDepartment of Nuclear Engineering, Polytechnic of Milan, Via Ponzio 34/3, 20133 Milan, Italy;bDepartment of Chemical and Nuclear Engineering, Polytechnic University of Valencia, Camí de Vera sn, 46022 Valencia, Spain
Abstract:This paper discusses the use of genetic algorithms (GA) within the area of reliability, availability, maintainability and safety (RAMS) optimization. First, the multi-objective optimization problem is formulated in general terms and two alternative approaches to its solution are illustrated. Then, the theory behind the operation of GA is presented. The steps of the algorithm are sketched to some details for both the traditional breeding procedure as well as for more sophisticated breeding procedures. The necessity of affine transforming the fitness function, object of the optimization, is discussed in detail, together with the transformation itself. In addition, how to handle constraints by the penalization approach is illustrated. Finally, specific metrics for measuring the performance of a genetic algorithm are introduced.
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