A Robust Design of Simulated Annealing Approach : Mixed-Model Sequencing Problem

시뮬레이티드 어닐링 알고리듬의 강건설계 : 혼합모델 투입순서 결정문제에 대한 적용

  • Kim, Ho-Gyun (Division of Mechanical & Industrial System Engineering, Dongeui University) ;
  • Paik, Chun-Hyun (Division of Mechanical & Industrial System Engineering, Dongeui University) ;
  • Cho, Hyung-Soo (Division of Mechanical & Industrial System Engineering, Dongeui University)
  • 김호균 (동의대학교 기계산업시스템공학부) ;
  • 백천현 (동의대학교 기계산업시스템공학부) ;
  • 조형수 (동의대학교 기계산업시스템공학부)
  • Received : 20020300
  • Accepted : 20020400
  • Published : 2002.06.30

Abstract

Simulated Annealing(SA) approach has been successfully applied to the combinatorial optimization problems with NP-hard complexity. To apply an SA algorithm to specific problems, generic parameters as well as problem-specific parameters must be determined. To overcome the embedded nature of SA, long computational time, some studies suggested the parameter design methods of determining SA related parameters. In this study, we propose a new parameter design approach based on robust design method. To show the effectiveness of the proposed method, the extensive computation experiments are conducted on the mixed-model sequencing problems.

Keywords

References

  1. Aarts, EH.I. and Van Laarhoven (1987), R.J.M., Simulated Annealing: Theory and Application, Reidel, Dordrecht
  2. Ali, M. M., Tom, A. and Viitanen, S.(2002), A direct search variant of the simulated annealing algorithm for optimization involving continuous variables, Computers & operations Research, 29, 87-102
  3. Bard, J. F., Shrub, A. and Joshi, S. B.(1994), Sequencing mixed-model assembly lines to level parts usage and minimize line length, International Journal of Production Research, 32, 2431-2454
  4. Bolat, A., Savsar, M. and A1-Fawzan, M. A.(1994), Algorithms for real-time scheduling of jobs on mixed model assembly lines, Computers and operation Research, 21, 487-498
  5. Celano, G., Fichera, 5., Grasso, V., La Conunare, U. and Perrone, G.(1999), An evolutionary approach to multi-objective scheduling of mixed model assembly lines, Computers and Industrial Engineering, 37, 69-73
  6. Cerny, V.(1985), Thermo dynamical approach to the traveling salesman problem: An efficient simulation algorithm, Journal of Optimization Theory and Applications, 45, 41-51
  7. Dar-El, E. M. (1978), Mixed model assembly line sequencing problem, OMEGA, 6, 313-323
  8. Huang, M. D., Romeo, F. and Sangiovanni-Vincentelli, A. I. (1986), An efficient general cooling schedule for simulated annealing, Proceedings of IEEE International Conference on Computer-Aided Design, Santa Clara, 381-384, November
  9. Ohnson, D.S., Aragon, C.R., Mc Geoch, I. A. and Schevon, C.(1989), Optimization by simulated annealing: An experimental evaluation; Part 1, Graph partitioning, operation Research, 37, 868-892
  10. Kim, Y. K., Hyun, C. J. and Kim, Y. H.(1996), Sequencing in mixed model assembly lines: a genetic algorithms approach, Computers and Operations Research, 23, 1131-1145
  11. Kirkpatrick, S., Gelatt, C. D. and Vecchi, M. P. (1983), Optimization by simulated annealing, Science, 220, 671-679
  12. Lundy, M. and Mees, A.(1986), Convergence of an annealing algorithm, Mathematical Programming, 34, 111-124
  13. McMullen, P. R.(1998), JIT sequencing for mixed-model assembly lines With setups using Tabu search, Production Planning and control, 9, 504-510
  14. McMullen, P. R. and Frazier, G. V. (2000), A simulated annealing approach to mixed-model sequencing with multiple objectives on a just-in-time line, IIE Transactions, 32, 679-686
  15. Miltenburg, J. (1989), Level schedules for mixed-model assembly lines in just-in-time production systems, Management Science, 35, 192-207
  16. Park, M. W. and Kim, Y. D.(1998), A systematic procedure for setting parameters in simulated annealing algorithms, Computers and Operations Research, 25, 207-217 https://doi.org/10.1016/S0305-0548(97)00054-3
  17. Su, C. T. and Hsieh, K. 1. (1998), Applying neural network approach to achieve robust design for dynamic quality characteristics, International Journal of Quality & Reliability Management, 15, 509-519
  18. Tamura,T., Long, H. and Ohno, K. (1999), A sequencing problem to level part usage rates and work loads for a mixed-model assembly line with a bypass subline, International Journal of Production Economics, 61, 557-564
  19. Youssef, G. S. and Vasant, B. R.(1991), Combinational optimization by stochastic evolution, IEEE Transactions on Computer-Aided Design, 10, 525-535