A multiobjective genetic algorithm approach to the optimization of the technical specifications of a nuclear safety system

Reliability Engineering and System Safety

Volumn 84, Issue 1, 2004, Pages 87-99

  Marseguerra, Marzio ^a   Zio, Enrico ^a   Podofillini, Luca ^a  

^a POLITECNICO DI MILANO   (Italy)

Author keywords

Allowable bypass time; Estimation uncertainties; Genetic algorithm; Multiobjective optimization; Nuclear safety system; Reactor protection instrumentation system; Risk informed decision making; Technical specifications

Indexed keywords

CONSTRAINT THEORY; DECISION MAKING; GENETIC ALGORITHMS; MAINTENANCE; NUCLEAR ENERGY; NUCLEAR POWER PLANTS; OPTIMIZATION; PUBLIC POLICY;

ALLOWABLE BYPASS TIME; ESTIMATION UNCERTAINTIES; MULTIOBJECTIVE OPTIMIZATION; NUCLEAR SAFETY SYSTEMS; REACTOR PROTECTION INSTRUMENTATION SYSTEM; RISK-INFORMED DECISION-MAKING; TECHNICAL SPECIFICATIONS;

SECURITY SYSTEMS;

EID: 1642586240     PISSN: 09518320     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0951-8320(03)00175-3     Document Type: Conference Paper

References (36)

1. Papazoglou I.A. Risk informed assessment of the technical specifications of PWR RPS instrumentation. Nucl Technol. 130:2000;329-350.
2. Use of probabilistic risk assessment methods in nuclear activities: final policy statement. Federal Register, vol. 60. US Nuclear Regulatory Commission; 1995. p. 42622.
3. Caruso M.A., Cheok M.C., Cunningham M.A., Holahan G.M., King T.L., Parry G.W., Rameysmith A.M., Rubin M.P., Thadani A.C. An approach for using risk assessment in risk-informed decisions on plant specific changes to the licensing basis. Reliab Engng Syst Safety. 63:1999;231.
4. Reference Safety Analysis Report RESAR-3S. Westinghouse Electric Corporation; 1975.
5. Jansen R.L., Lijewski L.M., Masarik R.J. Evaluation of the surveillance frequencies and out of service times for the reactor protection instrumentation system. WCA.P-10271. 1983;Westinghouse Electric Corporation.
6. Harunuzzaman M., Aldemir T. Optimisation of stand by safety system maintenance schedules in nuclear power plants. Nucl Technol. 113:1996;354.
7. Papazoglou I.A., Cho N.Z., Bari R.A. Reliability and risk allocation in nuclear power plants: a decision theoretic approach. Nucl Technol. 47:(3):1986;272-286.
8. Cho N.Z., Papazoglou I.A., Bari R.A. Multi-objective programming approach to reliability for nuclear power plants: a decision theoretic approach. Nucl Sci Engng. 95:(3):1987;165-188.
9. Jung WS, Cho NZ. Determination of performance criteria of safety systems in a nuclear power plant via simulated annealing optimisation method. PhD Thesis. Korea Advanced Institute of Science and Technology; 1993.
10. Martorell S., Carlos S., Sanchez A., Serradell V. Constrained optimization of test intervals using a steady-state genetic algorithm. Reliab Engng Syst Safety. 67:2000;215-232.
11. Munoz A., Martorell S., Serradell V. Genetic algorithms in optimizing surveillance and maintenance of components. Reliab Engng Syst Safety. 57:1997;107-120.
12. Marseguerra M., Zio E. Optimizing maintenance and repair policies via a combination of genetic algorithms and Monte Carlo simulation. Reliab Engng Syst Safety. 68:2000;69-83.
13. Yang J.-E., Sung T.-Y., Jin Y. Optimisation of the surveillance test interval of the safety systems at the plant level. Nucl Technol. 132:2000;352-365.
14. Marseguerra M, Zio E, Podofillini L. Optimal reliability/availability performance of uncertain systems via multiobjective genetic algorithms: a nuclear application. IEEE transactions on Reliablity, accepted for publication.
15. Marseguerra M., Podofillini L., Zio E. Using multiobjective genetic algorithms for the optimization of system performance in presence of parameters uncertainty. ESREL 2002. March 18-21, 2002;European Safety and Reliability, Lyon, France. p. 433-38 (Awarded the gold medal for best oral communication).
16. Coit D.W. System-reliability confidence-intervals for complex-systems with estimated component-reliability. IEEE Trans Reliab. 46:(4):1997;487-493.
17. Coit D.W., Smith A.E. Considering risk profiles in design optimization for series-parallel systems. IEEE Proc Annu Reliab Maintainability Symp. 1997;271-277.
18. Holland J.H. Adaptation in natural and artificial system. 1975;University of Michigan Press, Ann Arbor, MI.
19. Goldberg D.E. Genetic algorithms in search, optimization, and machine learning. 1989;Addison-Wesley, USA.
20. Beasly D., Bull D., Martin R. An overview on genetic algorithms. Part 1. Fundamentals. Univ Comput. 15:(2):1993;58-69.
21. Beasly D., Bull D., Martin R. An overview on genetic algorithms. Part 2. Research topics. Univ Comput. 15:(4):1993;170-181.
22. Fogel D. An introduction to simulated evolutionary optimization. IEEE Trans Neural Networks. 15:(1):1994;3-14.
23. Herrera F., Vergeday J.L. Genetic algorithm and soft computing. 1996;Ohysica-Verlag, Heidelberg.
24. Joyce P.A., Withers T.A., Hickling P.J. Application of genetic algorithms to optimum offshore plant design. Proceedings of ESREL 98, Trondheim (Norway). June 16-19, 1998;. p. 665-71.
25. Coit D.W., Smith A.E. Use of genetic algorithm to optimize a combinatorial reliability design problem. Proc Third IIE Res Conf. 1994;467-472.
26. Sawaragi Y., Nakayama H., Tanino T. Theory of multiobjective optimization. 1985;Academic Press, Orlando, FL.
27. Giuggioli Busacca P., Marseguerra M., Zio E. Multiobjective optimization by genetic algorithm: application to safety systems. Reliab Engng Syst Safety. 72:2001;59-74.
28. Zitzler E., Thiele L. Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach. IEEE Trans Evol Comput. 3:(4):1999;257-271.
29. Zitzler E. Evolutionary algorithms for multiobjective optimization: methods and applications. Swiss Federal Institute of Technology (ETH) Zurich. TIK-Schriftenreihe Nr. 30, Diss ETH No. 13398. 1999;Shaker Verlag, Germany. ISBN 3-8265-6831-1.
30. Fonseca C.M., Fleming P.J. An overview of evolutionary algorithms in multiobjective optimization. Evol Comput. 3:(1):1995;1-16.
31. Fonseca C.M., Fleming P.J. Genetic algorithms for multiobjective optimization: formulation, discussion and generalization. Forrest S. Genetic algorithms. Proceedings of the Fifth International Conference. 1993;Morgan Kaufmann, San Mateo, CA.
32. Srinivas N., Deb K. Multiobjective function optimization using nondominated sorting genetic algorithms. Evol Comput. 2:(3):1995;221-248.
33. Parks G.T. Multiobjective pressurized water reactor reload core design using genetic algorithm search. Nucl Sci Engng. 124:1997;178-187.
34. Toshinsky V.G., Sekimoto H., Toshinsky G.I. A method to improve multiobjective genetic algorithm optimization of a self-fuel-providing LMFBR by niche induction among nondominated solutions. Ann Nucl Energy. 27:2000;397-410.
35. Marseguerra M., Zio E. Basics of the Monte Carlo method with application to system reliability. 2002;Verlag GmbH, LiLoLe.
36. Marseguerra M., Zio E., Podofillini L. Condition-based maintenance optimization by means of genetic algorithms and Monte Carlo simulation. Reliab Engng Syst Safety. 77:2002;151-166.