Solution of stochastic multi-objective system reliability design problems using genetic algorithms

Advances in Safety and Reliability - Proceedings of the European Safety and Reliability Conference, ESREL 2005

Volumn 1, Issue , 2005, Pages 391-398

  Coit, David W ^a   Baheranwala, Fatema ^a  

^a RUTGERS UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONSTRAINT LIMITS; COST FLUCTUATION; DECISION MAKERS; ESTIMATION UNCERTAINTIES; MINIMUM COST; MULTI OBJECTIVE; MULTI-OBJECTIVE GENETIC ALGORITHM; OBJECTIVE FUNCTIONS; PARETO OPTIMAL SOLUTIONS; SYSTEM RELIABILITY; SYSTEM RELIABILITY DESIGN; TEST PROBLEM;

DECISION MAKING; STOCHASTIC SYSTEMS;

RELIABILITY;

EID: 33646532747     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (21)

1. Bulfin, R. & Liu, C. (1985). Optimal allocation of redundant components for large systems. IEEE Trans on Reliability, 34, 241-247.
2. Campbell, J.&Painton, L. (1996). Optimization of reliability allocation strategies through use of genetic algorithms. Proceedings of 6th Symposium on Multidisciplinary Design and Optimization, (pp. 1233-1242).
3. Chern, M. (1992). On the computational complexity of reliability redundancy allocation in a series system. Operations Research Letters, 11, 309-315.
4. Coit, D. & Smith, A. (1996). Reliability optimization of series-parallel systems using a genetic algorithm. IEEE Trans on Reliability, 46(4), 254-260.
5. Coit, D. (1997). System-Reliability Confidence Intervals for Complex SystemsWith Estimated Component Reliability. IEEE Trans on Reliability, 45(2), 254-260.
6. Coit, D. & Smith, A. (1998). Redundancy allocation to maximize a lower percentile of the system time-to-failure distribution. IEEE Trans on Reliability, 47(1), 79-87.
7. Coit, D. & A. Smith (1996). Solving the redundancy allocation problem using a combined neural network/GA approach; Computers & Operations Research, 23.
8. Coit, D., T. Jin, & N. Wattanapongsakorn (2004). System Optimization Considering Component Reliability Estimation Uncertainty: A Multi-Criteria Approach. IEEE Trans on Rel, 53(3).
9. Deb, K., T. Goel (2001). Controlled Elitist Non-Dominated Sorting Genetic Algorithm for Better Convergence. Evolutionary Multi-Criterion Optimization, Springer.
10. Ehrogott, M. & and X. Gandibleux (2000). A survey of annotated bibliography of multiobjective combinatorial optimization. OR Spektrum, 22.
11. Fyffe, D. E., Hines,W.W. & Lee, N. K. (1968). System reliability allocation and a computational algorithm. IEEE Trans on Reliability, 17, 64-69.
12. Gen, M., Ida, K. & Lee, J. U. (1990). A computational algorithm for solving 0-1 goal programming with GUB structures and its application for optimization problems in system reliability. Electronics and Communications in Japan, Part 3, 73, 88-96.
13. Goldberg, D. (1989). Genetic Algorithms in Search, Optimization and Machine Learning. Addison Wesley, Reading, MA.
14. Holland J. (1975). Adaptation in natural and artificial systems, U. Michigan Press, MI.
15. Ida, K., Gen M. & Yokota, T. (1994). System reliability optimization with several failure modes by genetic algorithm. In: Proceedings of 16th International Conference on Computers and Industrial Engineering, (pp 349-352).
16. Kulturel-Konak, S., A. Smith, & B. Norman (2004). Multi-Objective Tabu Search Using a Multinomial Probability Mass Function, European Journal of Operational Research.
17. Nakagawa, Y. & Miyazaki, S. (1981). Surrogate constraints algorithm for reliability optimization problems with two constraints. IEEE Trans on Reliability, R-30, 175-180.
18. Ogryczak, W. & A. Ruszczynski (2000). On consistency of stochastic dominance & mean-semideviation models. Math Programming, 89.
19. Painton, L.&Campbell, J. (1995). Genetic algorithms in optimization of system reliability. IEEE Trans on Reliability, 44(2), 172-178.
20. Srinivas, N. and K. Deb. Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms. Journal of Evolutionary Computation, 2(3).
21. Zitzler, E. & L. Thiele (1998). An evolutionary algorithm for multiobjective optimization: The strength Pareto approach.