Designing a risk-informed balanced system by genetic algorithms: Comparison of different balancing criteria

Reliability Engineering and System Safety

Volumn 93, Issue 12, 2008, Pages 1842-1852

  Podofillini, Luca ^a   Zio, Enrico ^b  

^a PAUL SCHERRER INSTITUTE   (Switzerland)

^b POLITECNICO DI MILANO   (Italy)

Author keywords

Birnbaum; Fusse Vesely; Genetic algorithms; Importance measures; Risk achievement worth; Risk informed test maintenance

Indexed keywords

ALGORITHMS; BIOELECTRIC PHENOMENA; DIESEL ENGINES; GENETIC ALGORITHMS; LEARNING SYSTEMS; MAINTENANCE; MULTIOBJECTIVE OPTIMIZATION; OCCUPATIONAL RISKS; PHILOSOPHICAL ASPECTS; REUSABILITY; RISK ASSESSMENT; SYSTEMS ANALYSIS;

BIRNBAUM; DESIGNING SYSTEMS; FUSSE-VESELY; GENETIC ALGORITHM (GA); IMPORTANCE MEASURES; INSPECTION AND MAINTENANCE; MAINTENANCE STRATEGIES; MULTI-OBJECTIVE OPTIMIZATION PROBLEM; OPTIMIZ ATION PROBLEMS; RISK ACHIEVEMENT WORTH; RISK-INFORMED TEST/MAINTENANCE; SYSTEM DESIGNS;

OPTIMIZATION;

EID: 49949103847     PISSN: 09518320     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ress.2008.03.015     Document Type: Article

References (30)

1. Vesely W.E., and Apostolakis G.E. Developments in risk-informed decision-making for nuclear power plants. Reliab Eng Syst Saf (1999) 223-224
2. NUREG/CR-6141, Handbook of methods for risk-based analyses of technical specifications, 1994.
3. Vesely W.E. Principles of resource-effectiveness and regulatory-effectiveness for risk-informed applications: reducing burdens by improving effectiveness. Reliab Eng Syst Saf (1999) 283-292
4. Use of probabilistic risk assessment methods in nuclear activities: final policy statement. Federal Register, US Nuclear Regulatory Commission, (August 1995); vol. 60. p. 42622.
5. Caruso M.A., Cheok M.C., Cunningham M.A., Holahan G.M., King T.L., Parry G.W., et al. An approach for using risk assessment in risk-informed decisions on plant-specific changes to the licensing basis. Reliab Eng Syst Saf (1999) 231-242
6. Cheok M.C., Parry G.W., and Sherry R.R. Use of importance measures in risk informed applications. Reliab Eng Syst Saf 60 (1998) 213-226
7. Birnbaum L.W. On the importance of different components in a multi-component system. Multivariate analysis vol. 2 (1969), Academic Press, New York
8. Fussell J.B. How to calculate system reliability and safety characteristics. IEEE Trans Reliab R-24 3 (1975) 169-174
9. Zio E., and Podofillini L. Importance measures and genetic algorithms for designing a risk-informed optimally balanced system. Reliab Eng Syst Saf 92 10 (2007) 1435-1447
10. Belegundu A.D., and Chandrupatla T.R. Optimization concepts and applications in engineering (1999), Prentice-Hall editions, Englewood, NJ (Chapter 11, p.373-81)
11. Holland J.H. Adaptation in natural and artificial system (1975), University of Michigan Press, Ann Arbor, MI
12. Goldberg D.E. Genetic algorithms in search, optimization and machine learning (1989), Addison-Wesley Publishing Company, Reading, MA
13. Levitin G, editor. Reliability engineering and system safety, Special Issue-Genetic Algorithms and Reliability 2006; 91 (9): p. 975-1104.
14. Levitin Gregory, editor. Genetic algorithms and Monte Carlo simulation for the optimization of system design and operation. ISBN: 978-3-540-37367-4 (2007).
15. Joyce PA, Withers TA, Hickling PJ. Application of Genetic algorithms to optimum offshore plant design. In: Proceedings of ESREL 98, Trondheim (Norway), June 16-19, 1998, p. 665-71.
16. Martorell S., Carlos S., Sanchez A., and Serradell V. Constrained optimization of test intervals using a steady-state genetic algorithm. Reliab Eng Syst Saf 67 (2000) 215-232
17. Munoz A., Martorell S., and Serradell V. Genetic algorithms in optimizing surveillance and maintenance of components. Reliab Eng Syst Saf 57 (1997) 107-120
18. Marseguerra M., and Zio E. Optimizing maintenance and repair policies via a combination of genetic algorithms and Monte Carlo simulation. Reliab Eng Syst Saf 68 (2000) 69-83
19. Coit D.W., and Smith A.E. Reliability optimization of series-parallel systems using a genetic algorithm. IEEE Trans Reliab 45 2 (1996) 254-260
20. Harunuzzaman M., and Aldemir T. Optimization of standby safety system maintenance schedules in nuclear power plants. Nucl Technol 113 (1996) 354-367
21. Giuggioli Busacca P., Marseguerra M., and Zio E. Multiobjective optimization by genetic algorithm: application to safety systems. Reliab Eng Syst Saf 72 (2001) 59-74
22. Zitzler E., and Thiele L. Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach. IEEE Trans Evol Comput 3 4 (1999) 257-271
23. 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. 3-8265-6831-1
24. Fonseca C.M., and Fleming P.J. An overview of evolutionary algorithms in multiobjective optimization. Evol Comput 3 1 (1995) 1-16
25. Fonseca C.M., and Fleming P.J. Genetic algorithms for multiobjective optimization: formulation, discussion and generalization. In: Forrest S. (Ed). Genetic algorithms: proceedings of the fifth international conference (1993), Morgan Kaufmann, San Mateo, CA
26. Srinivas N., and Deb K. Multiobjective function optimization using nondominated sorting genetic algorithms. Evol Comput 2 3 (1995) 221-248
27. Parks G.T. Multiobjective pressurized water reactor reload core design using genetic algorithm search. Nucl Sci Eng 124 (1997) 178-187
28. Toshinsky V.G., Sekimoto H., and 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
29. Sawaragi Y., Nakayama H., and Tanino T. Theory of multiobjective optimization (1985), Academic Press, Orlando, Florida
30. Apostolakis G., and Chu T.L. The unavailability of systems under periodic test and maintenance. Nucl Technol 50 (1980) 5-15