Journal of Korean Institute of Industrial Engineers (대한산업공학회지)

Korean Institute of Industrial Engineers (대한산업공학회)
권호 표지

Solution Methods for Reliability Optimization of a Series System with Component Choices

부품선택이 존재하는 직렬시스템의 신뢰성 최적화 해법

  • Kim, Ho-Gyun (Department of Industrial & Management Engineering, Dong-Eui University) ;
  • Bae, Chang-Ok (The 3rd R&D Institute-2, Agency for Defense Development) ;
  • Kim, Jae-Hwan (Division of Nano Data System, Korea Maritime University) ;
  • Son, Joo-Young (Division of Computer, Control, and Electronic Communications Engineering, Korea Maritime University)
  • 김호균 (동의대학교 산업경영공학과) ;
  • 배창옥 (국방과학연구소 제2기술연구본부 2부) ;
  • 김재환 (한국해양대학교 나노데이터시스템학부) ;
  • 손주영 (한국해양대학교 컴퓨터.제어.전자통신공학부)
  • Published : 2008.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

Reliability has been considered as an important design measure in various industrial systems. We discuss a reliability optimization problem with component choices (ROP-CC) subject to a budget constraint. This problem has been known as a NP-hard problem in the reliability design fields. Several researchers have been working to find the optimal solution through different heuristic methods. In this paper, we describe our development of simulated annealing (SA) and tabu search (TS) algorithms and a reoptimization procedure of the two algorithms for solving the problem. Experimental results for some examples are shown to evaluate the performance of these methods. We compare the results with the solutions of a previous study which used ant system (AS) and the global optimal solution of each example obtained through an optimization package, CPLEX 9.1. The computational results indicate that the developed algorithms outperform the previous results.

Keywords

References

  1. Cardoso, M. F., Salcedo, R. L. and de Azevedo, S. F. (1994), Nonequilibrium simulated annealing : a faster approach to combinatorial minimization, Industrial Engineering Chemical Research, 33, 1908-1918. https://doi.org/10.1021/ie00032a005
  2. Cerny, V. (1985), Thermodynamical approach to the traveling salesman problem : An efficient simulation algorithm, Journal of Optimization Theory and Applications, 45, 41-51. https://doi.org/10.1007/BF00940812
  3. Chen, T. C. and You, P. S. (2005), Immune algorithms-based approach for redundant reliability problems with multiple component choices, Computers in Industry, 56, 195-205. https://doi.org/10.1016/j.compind.2004.06.002
  4. Coit, D. E. and Smith, A. E. (1996a), Reliability optimization of series- parallel systems using a genetic algorithm, IEEE Transactions on Reliability, 45(2), 254-260. https://doi.org/10.1109/24.510811
  5. Coit, D. E. and Smith, A. E. (1996b), Penalty guided genetic search for reliability design optimization, Computers & Industrial Engineering, 30(4), 895-904. https://doi.org/10.1016/0360-8352(96)00040-X
  6. Fyffe, D. E., Hines, W. W. and Lee, N. K. (1968), System reliability allocation and a computational algorithm, IEEE Transactions on Reliability, 17, 64-69. https://doi.org/10.1109/TR.1968.5217517
  7. Glover, F. (1986), Future paths for integer programming and links to artificial intelligence, Computers and Operations Research, 13, 533-549. https://doi.org/10.1016/0305-0548(86)90048-1
  8. Glover, F. and Kochenberger, G. A. (2001), Handbook of Metaheuristics, Kluwer Academic Pub.
  9. Hsieh, Y. C. (2002), A linear approximation for redundant reliability problems with multiple component choices, Computers & Industrial Engineering, 44, 91-103.
  10. ILOG, Inc. (2007), ILOG CPLEX, http://www.ilog.com/products/ cplex/.
  11. Jain, A. S. and Meeran, S. (1999), Deterministic job shop scheduling: past, present and future, European Journal of Operational Research, 113, 390-434. https://doi.org/10.1016/S0377-2217(98)00113-1
  12. Kim, H. G., Bae, C. O. and Paik, C. H. (2004), A simulated annealing algorithm for the optimal reliability design problem of a series system with multiple component choices, IE Interfaces, 17(Special Edition), 69-78.
  13. Kirkpatrick, S., Gelatt, C. D. and Vecchi, M. P. (1983), Optimization by simulated annealing, Science, 220, 671-679. https://doi.org/10.1126/science.220.4598.671
  14. Kulturel-Konak, S., Smith, A. E. and Coit, D. W. (2003), Efficiently solving the redundancy allocation problem using tabu search. IIE Transactions, 35, 515-526. https://doi.org/10.1080/07408170304422
  15. Kulturel-Konak, S., Norman, B. A., Coit, D. W. and Smith, A. E. (2004), Exploiting tabu search memory in constrained problem, INFORMS Journal on Computing, 16(3), 241-254. https://doi.org/10.1287/ijoc.1030.0040
  16. Kuo, W., Prasad, V. R., Tillman, F. A. and Hwang, C. L. (2001), Optimal Reliability Design : Fundamentals and Applications, Cambridge University Press, Cambridge.
  17. Liang, Y. C. and Smith, A. E. (2004), Ant colony optimization algorithm for the redundancy allocation problem (RAP), IEEE Transactions on Reliability, 53(3), 417-423. https://doi.org/10.1109/TR.2004.832816
  18. Metropolis, N., Rosenbluth, A., Rosenbluth, M., Teller, A. and Teller, E. (1953), Equation of state calculations by fast computing machines, Journal of Chemical Physics, 21, 1087-1092. https://doi.org/10.1063/1.1699114
  19. Nahas, N. and Nourelfath, M. (2005), Ant system for reliability optimization of a series system with multiple-choice and budget constraints, Reliability Engineering and System Safety, 87, 1-12. https://doi.org/10.1016/j.ress.2004.02.007
  20. Nahas, N., Nourelfath, M. and Ait-Kadi, D. (2007), Coupling ant colony and the degraded ceiling algorithm for the redundancy allocation problem of series-parallel systems, Reliability Engineering and System Safety, 92, 211-222. https://doi.org/10.1016/j.ress.2005.12.002
  21. Nakagawa, Y. and Miyazaki, S. (1981), Surrogate constraints algorithm for reliability optimization problems with two constraints, IEEE Transactions on Reliability, 30(2), 175-180. https://doi.org/10.1109/TR.1981.5221024
  22. Ramirez-Marquez, J. E. and Coit, D. W. (2004), A heuristic for solving the redundancy allocation problem for multiple-state series-parallel systems, Reliability Engineering and System Safety, 83, 341-349. https://doi.org/10.1016/j.ress.2003.10.010
  23. Ravi, V., Muty, B. and Reddy, P. (1997), Nonequilibrium simulatedannealing algorithm applied reliability optimization of complex systems, IEEE Transactions on Reliability, 46(2), 233-239. https://doi.org/10.1109/24.589951
  24. Sung, C. S. and Cho, Y. K. (2000), Reliability optimization of a series system with multiple-choice and budget constraint, European Journal of Operational Research, 127, 159-171. https://doi.org/10.1016/S0377-2217(99)00330-6
  25. Yokota, T., Gen, M. and Li, Y. X. (1996), Genetic algorithm for nonlinear mixed-integer programming and its applications, Computers & Industrial Engineering, 30(4), 905-917. https://doi.org/10.1016/0360-8352(96)00041-1
  26. Zhang, C. Y., Li, P. G., Rao, Y. Q. and Guan, Z. L. (2008), A very fast TS/SA algorithm for the job shop scheduling problem, Computers & Operations Research, 35, 282-294. https://doi.org/10.1016/j.cor.2006.02.024
  27. Zhao, J. H., Liu, Z. and Dao, M. T. (2007), Reliability optimization using multiobjective ant colony system approaches, Reliability Engineering and System Safety, 92, 109-120. https://doi.org/10.1016/j.ress.2005.12.001