전처리 방식의 복수지역 제약공정 스케줄링

Preprocessing based Scheduling for Multi-Site Constraint Resources

  • 발행 : 2008.03.31

초록

Make-to-order manufacturers with multiple plants at multiple sites need to have the ability to quickly determine which plant will produce which customer order to meet the due date and minimize the transportation cost from the plants to the customer. Balancing the work loads and minimizing setups and make-span are also of great concern. Solving such scheduling problems usually takes a long time. We propose a new approach, which we call 'preprocessing', for resolving such complex problems. In preprocessing scheme, a 'good' a priori schedule is prepared and maintained using unconfirmed order information. Upon the confirmation of orders. the preprocessed schedule is quickly modified to obtain the final schedule. We present a preprocessing solution algorithm for multi-site constraint scheduling problem (MSCSP) using genetic algorithm; and conduct computational experiments to evaluate the performance of the algorithm.

키워드

참고문헌

  1. 김석준, 이채영, '작업일정계획문제 해결을 위한 유전알고리듬의 응용,' 한국경영학회지, 제17권, 제3호(1992), pp.1-12
  2. Atwater, J.B. and Chakravorty, S.S., 'A study of the utilization of capacity constrained resources in drum-buffer-rope systems,' Production and Operations Management, Vol.11, No.2(2002), pp.259-269 https://doi.org/10.1111/j.1937-5956.2002.tb00495.x
  3. Feldmann, M. and Biskup, D., 'Single-machine scheduling for minimizing earliness and tardiness penalties by meta-heuristic approaches,' Computers and Industrial Engineering, Vol.44 (2003), pp.307-323 https://doi.org/10.1016/S0360-8352(02)00181-X
  4. Ghedjati, F., 'Genetic algorithms for the jobshop scheduling problem with unrelated parallel constraints:Heuristic mixing method machines and precedence,' Computers and Industrial Engineering, Vol.37(1999), pp.39-42 https://doi.org/10.1016/S0360-8352(99)00019-4
  5. Koonce, D.A. and Tsai, S.C., 'Using data mining to find patterns in genetic algorithm solutions to a job shop schedule,' Computers and Industrial Engineering, Vol. 38(2000), pp.361-374 https://doi.org/10.1016/S0360-8352(00)00050-4
  6. Kutanoglu, E. and Wu, S., 'Improving scheduling robustness via preprocessing and dynamic adaptation,' IIE transactions, Vol.36, No.11(2004), pp.1107-1124 https://doi.org/10.1080/07408170490500681
  7. Liu, J. and Tang, L., 'A modified genetic algorithm for single machine scheduling,' Computers and Industrial Engineering, Vol. 37(1999), pp.43-46 https://doi.org/10.1016/S0360-8352(99)00020-0
  8. Simons, J.V., Simpson, W.P., and Carlson, J.J., 'Formulation and solution of the drumbuffer- rope constraint scheduling problem (DBRCSP),' Int. J. of Production Research, Vol.34, No.(1996), pp.2405-2420 https://doi.org/10.1080/00207549608905035
  9. Simons, J.V., Stephens, M.D., and Simpson, W.P., 'Simultaneous versus sequential scheduling of multiple resources which constrain system throughput,' Int. J. of Production Research, Vol.37, No.1(1999), pp.21-33 https://doi.org/10.1080/002075499191896
  10. Srikanth M.L. and Umble, M.M., Synchronous management:profit-based manufacturing for the 21st century, The Spectrum Publishing Co. 1997
  11. Steele, D.C., Philipoom, P.R., Malhotra, M.K., and Fry, T.D., 'Comparison between drum-buffer-rope and material requirements planning:a case study,' Int. J. of Production Research, Vol.43, No.15(2005), pp.3181-3208 https://doi.org/10.1080/00207540500076704
  12. Uzsoy, R. and Wang, C. S., 'Performance of decomposition procedures for job shop scheduling problems with bottleneck machines,' Int. J. of Production Research, Vol.38, No.6(2000), pp.1271-1286 https://doi.org/10.1080/002075400188843
  13. Yu, H. and Liang, W., 'Neural network and genetic algorithm-based hybrid approach to expanded job-shop scheduling,' Computers and Industrial Engineering, Vol.39(2001), pp.337-356 https://doi.org/10.1016/S0360-8352(01)00010-9
  14. Wu, H.H. and Yeh, M.L., 'A DBR scheduling method for manufacturing environments with bottleneck re-entrant flows,' International Journal of Production Research, Vol.44, No.5(2006), pp.883-902 https://doi.org/10.1080/00207540500362187