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References
Bäck, T., Evolutionary Algorithms in Theory and Practice. Evolution Strategies, Evolutionary Programming, Genetic Algorithms (1996), Oxford University Press, NY.
Barata, J., Soares, C.G., Marseguerra, M., Zio, E. (2002). Simulation modelling of repairable multi-component deteriorating systems for ‘on condition’ mainte-nance optimisation. Reliability Engineering & System Safety 76, 255-264.
Beasley, D., Bull, D., Martin, R. (1993a). An overview of genetic algorithms: part 1, fundamentals, University Computing 15:2, 58-69.
Beasley, D., Bull, D., Martin, R. (1993b). An overview of genetic algorithms: part 2, research topics, University Computing 15:4, 170-181.
Borgonovo, E., Marseguerra, M., Zio, E. (2000). A Monte Carlo methodological approach to plant availability modeling with maintenance, aging and obsoles-cence. Reliability Engineering & System Safety 67, 61-73.
Bris, R., Chayelet, E. (2003). New method to minimize the preventive mainte-nance cost of series-parallel systems. Reliability Engineering & System Safety. 82 247-225.
Bunea, C., Bedford, T. (2002). The effect of model uncertainty on maintenance optimization. IEEE Transactions on Reliability. 51/4: 486-493.
Busacca, P.G., Marseguerra, M., Zio, E. (2001). Multiobjective optimization by genetic algorithms: application to safety systems. Reliability Engineering & System Safety 72, 59-74.
Cantoni, W., Marseguerra, M., Zio, E. (2000). Genetic algorithms and Monte Carlo simulation for optimal plant design. Reliability Engineering & System Safety 2000; 68(1): 29-38.
Carlson, S. (1995). A General Method for Handling Constraints in Genetic Algo-rithms. University of Virginia.
Carlson, S., Shonkwiler, R., Babar, S., and Aral, M. (1995). Annealing a Genetic Algorithm over Constraints. University of Virginia.
Cepin, M. (2002). Optimization of safety equipment outages improves safety. Rel. Engng & System Safety; 77(1): 71-80.
Coit, D.W., Jin, T.D., and Wattanapongsakorn, N. (2004). System optimization with component reliability estimation uncertainty: A multi-criteria approach. IEEE Transactions on Reliability. 53:3, 369-380.
Coit, D.W., and Baheranwala, F. (2005). Solution of stochastic multi-objective system reliability design problems using genetic algorithms. In Proceedings of ESREL Conference 2005, Ed. Kolowrocki, Tri City, Poland, 391-398.
Davis, L., (Ed.) (1991). Handbook of Genetic Algorithms, Van Nostrand Reinholt, NY.
Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T. (2002). A fast and elitist mul-tiobjective genetic algorithm. NSGA-II. IEEE Transactions on Evolutionary Computation 6(2), 182-197.
De Jong, K. (1975). An analysis of the behaviour of a class of genetic adaptive systems, PhD thesis, University of Michigan, 1975.
Elegbede, C., Adjallah, K. (2003). Availability allocation to repairable systems with genetic algorithms: a multi-objective formulation. Reliability Engineer-ing & System Safety. 82, 319-330.
Fogel, D. (1994). An introduction to simulated evolutionary optimization. IEEE Transactions on Neural Networks 15:1, 3-14.
Fogel, D.B. (1995). Evolutionary Computation, IEEE Press, NY.
Fonseca, C.M., and Fleming, P.J. (1993). Genetic algorithms for multiobjective optimization: Formulation, discussion and generalization. In S. Forrest (Ed.), Proceedings of the Fifth International Conference on Genetic Algorithms, San Mateo, California, pp. 416-423. Morgan Kaufmann.
Goldberg, D.E., (1989). Genetic algorithms in search, optimization and machine learning. Addison-Wesley Pub. Co. Reading MA.
Haruzunnaman, M., Aldemir, T. (1996). Optimization of standby safety system maintenance schedules in nuclear power plants. Nucl. Technol 1996; 113(3): 354-367.
Herrera, F. and Verdegay, J.L., (Eds.) (1996). Genetic Algorithms and Soft Com-puting, Physica-Verlag Heidelberg.
Holland, J. (1975). Adaptation in Natural and Artificial Systems, Ann Arbor, Uni-versity of Michigan Press.
Horn, J., Nafpliotis, N., and Goldberg, D.E. (1994). A niched pareto genetic algo-rithm for multiobjective optimization. In Proceedings of the First IEEE Conference on Evolutionary Computation, IEEE World Congress on Compu-tational Computation, Volume 1, Piscataway, NJ, pp. 82-87. IEEE Press.
Joines, J.A., and Houck, C.R. (1994). On the Use of Non-Stationary Penalty Func-tions to Solve Nonlinear Constrained Optimization Problems With GAs. In Proceedings of the Evolutionary Computation Conference-Poster Sessions, part of the IEEE World Congress on Computational Intelligence, Orlando, 26-29 June 1994, 579-584.
Joon-Eon Yang, Tae-Yong Sung, Youngho Jin. (2000). Optimization of the Sur-veillance Test Interval of the Safety Systems at the Plant Level. Nuclear Technology. 132, 352-365.
Knowles, J.D., and Corne D.W. (1999). The pareto archived evolution strategy: A new baseline algorithm for pareto multiobjective optimisation. In Congress on Evolutionary Computation (CEC99), Volume 1, Piscataway, NJ, pp. 98-105. IEEE Press.
Kumar, A., Pathak, R., Grupta, Y. (1995). Genetic-algorithms-based reliability op-timization for computer network expansion. IEEE Transactions on Reliability 44:1, 63-68.
Kursawe, F. (1991). A variant of evolution strategies for vector optimization. In H.-P. Schwefel and R. Männer, editors, Parallel Problem Solving from Nature - Proc. 1st Workshop PPSN, pages 193-197, Berlin, Springer.
Lapa, C.M.F., Pereira, C.M.N.A., and Melo, P.F.F.E. (2000). Maximization of a nuclear system availability through maintenance scheduling optimization us-ing a genetic algorithm. Nuclear engineering and design, 196, 219-231.
Lapa, C.M.F., Pereira, C.M.N.A., Melo, P.F.F.E. (2003). Surveillance test policy optimization through genetic algorithms using non-periodic intervention fre-quencies and considering seasonal constraints. Rel. Engng. and System Safety; 81(1): 103-109.
Lapa, C.M.F., Pereira, C.M.N.A. (2006). A model for preventive maintenance plan-ning by genetic algorithms based in cost and reliability. Rel. Engng. and Sys-tem Safety; 91(2): 233-240.
Laumanns, M., Thiele, L., Deb, K., and Zitzler, E. (2002). Archiving with Guaran-teed Convergence And Diversity in Multi-objective Optimization. In GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference, Morgan Kaufmann Publishers, New York, NY, USA, pages 439-447, July, 2002.
Leemis, L. (1995). Reliability. Probabilistic Models and Statistical Methods, Pren-tice-Hall, Englewood Cliffs, New Jersey.
Levitin, G., and Lisnianski, A. (1999). Joint redundancy and maintenance optimi-zation for multistate series-parallel systems. Reliability Engineering & Sys-tem Safety 64, 33-42.
Levitin, G., and Lisnianski, A. (2000). Optimization of imperfect preventive maintenance for multi-state systems. Reliability Engineering & System Safety 67, 193-203.
Marseguerra, M., Zio, E. (2000). Optimizing maintenance and repair policies via a combination of genetic algorithms and Monte Carlo simulation. Reliability Engineering & System Safety; 68(1): 69-83.
Marseguerra, M., Zio, E., and Podofillini L. (2002). Condition-based maintenance optimization by means of genetic algorithms and Monte Carlo simulation. Re-liability Engineering & System Safety 77, 151-166.
Marseguerra, M., Zio, E., and Podofillini L. (2004a). A multiobjective genetic algorithm approach to the optimization of the technical specifications of a nuclear safety system. Reliability Engineering & System Safety 84, 87-99.
Marseguerra, M., Zio, E., and Podofillini, L. (2004b). Optimal reliability/ availability of uncertain systems via multi-objective genetic algorithms. Ieee Transactions on Reliability 53, 424-434.
Marseguerra, M., Zio, E., and Podofillini L. (2004c). A multiobjective genetic algorithm approach to the optimization of the technical specifications of a nuclear safety system. Reliability Engineering & System Safety; 84(1):87-99.
Marseguerra, M., Zio, E., and Podofillini, L. (2004d). Optimal reliability/availability of uncertain systems via multi-objective genetic algorithms. Ieee Transactions on Reliability; 53(3): 424-434.
Marseguerra, M., Zio, E., and Martorell, S. (2006). Basics of genetic algorithms optimization for RAMS applications. Reliability Engineering & System Safety. In press.
Martorell, S., Serradell, V., and Samanta, P.K. (1995). Improving allowed outage time and surveillance test interval requirements: a study of their interactions using probabilistic methods. Rel. Engng & System Safety, 47, 119-129.
Martorell, S., Carlos, S., Sanchez, A., and Serradell, V. (2000). Constrained opti-mization of test intervals using a steady-state genetic algorithm. Rel. Engng. and System Safety 67(3): 215-232.
Martorell, S., Carlos, S., Sanchez, A., and Serradell, V. (2002). Simultaneous and multi-criteria optimization of TS requirements and Maintenance at NPPs. Ann. of Nucl. Energy, 29(2): 147-168.
Martorell, S., Sanchez, A., Carlos, S., and Serradell, V. (2004). Alternatives and challenges in optimizing industrial safety using genetic algorithms. Reliab Eng Syst Safety; 86, 25-38.
Martorell, S., Villanueva, J.F., Carlos, S., Nebot, Y., Sánchez, A., Pitarch, J.L., and Serradell, V. (2005). RAMS+C informed decision-making with applica-tion to multi-objective optimization of technical specifications and mainte-nance using genetic algorithms. Reliab Eng System Safety 87/1: 65-75.
Martorell, S., Carlos, S., Villanueva, J.F., Sanchez, A.I., Galvan, B., Salazar, D., and Cepin M. (2006). Use of multiple objective evolutionary algorithms in optimizing surveillance requirements. Reliability Engineering & System Safety. In press.
McCormick, N.J. (1981). Reliability and Risk Analysis. Methods and Nuclear Power Application. EEUU: Academic Press.
Michalewicz, Z. (1995). A survey of constraint handling techniques in evolution-ary computation methods. In Proceedings of the Fourth International Confer-ence on Evolutionary Programming, Ed. McDonnell, J.R. Reynolds, R.G. Fogel, D.B., San Diego, CA., pp. 135-155.
Michalewicz, Z. Genetic Algorithms + Data Structures = Evolution Programs (3 Ed.) (1996), Springer-Verlag, Berlin.
Muñoz, A., Martorell, S., and Serradell, V. (1997). Genetic algorithms in optimiz-ing surveillance and maintenance of components. Rel. Engng. and System Safety; 57(2): 107-120.
Naujoks, B. (2005). Enhanced Evolutionary Algorithms for Industrial Applica-tions. In Proceedings of Evolutionary and Deterministic Methods for Design, Optimization and Control with Applications to Industrial and Societal Prob-lems EUROGEN 2005, FLM, Munich.
Neittaanmaki, P. (2005). Hybrid optimization methods for industrial problems. In Proceedings of Evolutionary and Deterministic Methods for Design, Optimi-zation and Control with Applications to Industrial and Societal Problems EUROGEN 2005, FLM, Munich.
Painton, L., and Campbell, J. (1995). Genetic algorithms in optimization of system reliability. IEEE Transactions on Reliability 44:2, 172-178.
Pereira, C.M.N.A., and Lapa, C.M.F. (2003). Parallel island genetic algorithm applied to a nuclear power plant auxiliary feedwater system surveillance tests policy optimization. Annals of Nuclear Energy; 30, 1665-1675.
Podofillini, L., Zio, E., Vatn, J., and Vatn, J. (2006). Risk-informed optimisation of railway tracks inspection and maintenance procedures. Reliability Engi-neering & System Safety In press 91(1) 20-35.
Rocco, C.M., Miller, A.J., Moreno, J.A., Carrasquero, N., and Medina, M. (2000). Sensitivity and uncertainty analysis in optimization programs using an evolu-tionary approach: a maintenance application. Reliability Engineering & Sys-tem Safety. 67(3) 249-256.
Rocco, C.M. (2002). Maintenance optimization under uncertainties using interval methods & evolutionary strategies. In Annual Reliability and Maintainability Symposium. 254-259.
Salazar, D., Martorell, S., and Galván, B. (2005). Analysis of representation alter-natives for a multiple-objective floating bound scheduling problem of a nuclear power plant safety system. In Proceedings of Evolutionary and De-terministic Methods for Design, Optimization and Control with Applications to Industrial and Societal Problems EUROGEN 2005, FLM, Munich.
Sasaki, D. (2005). Adaptive Range Multi-Objective Genetic Algorithms and Self-Organizing Map for Multi-Objective Optimization Problem. In Proceedings of Evolutionary and Deterministic Methods for Design, Optimization and Control with Applications to Industrial and Societal Problems EUROGEN 2005, FLM, Munich.
Schaffer, J.D. (1985). Multiple objective optimization with vector evaluated ge-netic algorithms. In J.J. Grefenstette (Ed.), Proceedings of an International Conference on Genetic Algorithms and Their Applications, Pittsburgh, PA, pp. 93-100. sponsored by Texas Instruments and U.S. Navy Center for Ap-plied Research in Artificial Intelligence (NCARAI).
Srinivas, N., and Deb, K. (1994). Multiobjective optimization using nondominat-edsorting in genetic algorithms. Evolutionary Computation 2(3), 221-248.
Tsai, Y., Wang, K., and Teng, H. (2001). Optimizing preventive maintenance for mechanical components using genetic algorithms. Reliability Engineering & System Safety 74, 89-97.
Tong, J., Mao, D., and Xue, D. (2004). A genetic algorithm solution for a nuclear power plant risk-cost maintenance model. Nuclear engineering and design. 229, 81-89.
Utyuzhnikov, S.V. (2005). Numerical Method for Generating the Entiere Pareto Frontier in Multiobjective Optimization. In Proceedings of Evolutionary and Deterministic Methods for Design, Optimization and Control with Applica-tions to Industrial and Societal Problems EUROGEN 2005, FLM, Munich.
Vesely, W. (1999). Principles of resource-effectiveness and regulatory-effective-ness for risk-informed applications: Reducing burdens by improving effec-tiveness. Rel. Engng & System Safety; 63, 283-292.
Vinod, G., Kushwaha, A.W. (2004). Optimisation of ISI interval using genetic al-gorithms for risk informed in-service inspection. Rel. Engng & System Safety; 86, 307-316.
Winter, G., Galván, B., Alonso, S., and Mendez, M. (2005). New Trends in Evolu-tionary Optimization and its Impact on Dependability Problems. In Proceed-ings of Evolutionary and Deterministic Methods for Design, Optimization and Control with Applications to Industrial and Societal Problems EUROGEN 2005, FLM, Munich.
Yang, J-E., Hwang, M-J., Sung, T-Y, and Jin, Y. (1999). Application of genetic algorithm for reliability allocation in nuclear power plants. Reliability Engi-neering & System Safety 1999, (65) 229-238.
Zitzler E. (1999). Evolutionary Algorithms for Multiobjective Optimization: Methods and Applications. PhD Thesis. Swiss Federal Institute of Technol-ogy, Zurich.
Zitzler E., Laumanns M. and Thiele L. (2001). SPEA2: Improving the strength pareto evolutionary algorithm. TIK-report 2001. Computer Engineering and Networks Lab (TIK) Swiss Federal Institute of Technology. Zurich. (http://www.tik.ee.ethz.ch/~zitzler/).
Zitzler, E., Laumanns, M., Thiele, L., Fonseca, C.M. And Grunert da Fonseca, V. (2003). Performance Assessment of Multiobjective Optimizers: An Analysis and Review. IEEE Transactions on Evolutionary Computation 7(2), pp 117-132.
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Martorell, S., Carlos, S., Villanueva, J.F., Sánchez, A. (2007). Genetic Algorithm Applications in Surveillance and Maintenance Optimization. In: Levitin, G. (eds) Computational Intelligence in Reliability Engineering. Studies in Computational Intelligence, vol 39. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37368-1_3
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