대한산업공학회지 (Journal of Korean Institute of Industrial Engineers)

  • 제30권2호
  • /
  • Pages.159-164
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  • 2004
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  • 1225-0988(pISSN)
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  • 2234-6457(eISSN)
대한산업공학회 (Korean Institute of Industrial Engineers)
권호 표지

딜리버리 윈도우 로트-스트리밍 흐름 공정 문제

Lot-Streaming Flow Shop Problem with Delivery Windows

  • 윤석훈 (숭실대학교 산업정보시스템공학과)
  • Yoon, Suk-Hun (Department of Industrial and Information Systems Engineering, Soongsil University)
  • 발행 : 2004.06.30
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초록

Lot-streaming is the process of splitting a job (lot) into a number of smaller sublots and then scheduling these sublots in order to accelerate the completion of jobs in a multi-stage production system. Anew genetic algorithm (NGA) is proposed for an-job, m-machine, equal-size sublot lot-streaming flow shop scheduling problem with delivery windows in which the objective is to minimize the mean weighted absolute deviation of job completion times from due dates. The performance of NGA is compared with that of an adjacent pairwise interchange (API) method and the results of computational experiments show that NGA works well for this type of problem.

키워드

참고문헌

  1. Baker, K.R. and Pyke, D.F. (1990), Solution procedures for the lot-streaming problem, Decision Sciences, 21, 475-491
  2. Baker, K.R. (1974), Introduction to Sequencing and Scheduling, Wiley, New York
  3. Beasley, D., Bull, D.R., and Martin, R.R. (1993),An overview of genetic algorithms: part I, fundamentals, University Computing, 15, 58-69
  4. Garey, M.R. and John, D.S. (1979), Computers and Intractability: A Guide to the Theory of NP-completeness, Freeman, San Francisco, CA
  5. Glass, C.A., Gupta, J.N.D., and Potts, C.N. (1994), Lot streaming in three-stage production processes, European Journal of Operational Research, 75, 378-394
  6. Goldberg, D.E.(1989), Genetic Algorithms in Search, Optimization. and Machine Learning, Addison-Wesley Publishing Company, New York, NY
  7. Hall, N.G. and Posner, M.E. (1991), Earliness-tardiness scheduling problems, I: weighted deviation of completion times about a common due date, Operations Research, 39(5), 836-846 https://doi.org/10.1287/opre.39.5.836
  8. Hall, N.G. and Posner, M.E. (2001), Generating experimental data for computational testing with machine scheduling applications, Operations Research, 49, 854-865
  9. Liepins, G.E. and Hilliard, M.R. (1989), Genetic algorithms: foundation and applications, Annals of Operations Research, 21, 31-58
  10. Reeves, C.R. (1995), A genetic algorithm for flowshop sequencing, Computers and Operations Research, 22(1), 5-13 https://doi.org/10.1016/0305-0548(93)E0014-K
  11. Reiter, S. (1966), A system for managing job-shop production, The Journal of Business, 34, 371-393
  12. Solomon, M.M. and Desrosiers, J. (1988), Time window constrained routing and scheduling problems, Transportation science, 22(I), 1-13
  13. Srinivas, M. and Patnaik, L.M. (1994), Genetic algorithms: a survey, Computer, 27, 17-26
  14. Ventura, J.A. and Weng, M.X. (1996), Single machine scheduling with a common delivery window, Journal of the Operational Research Society, 47, 424-434
  15. Wagner, B.J. and Ragatz, G.L. (1994), The impact of lot splitting on due date performance, Journal of Operations Management, 12, 13-25
  16. Weng, M.X. and Ventura, J.A. (1995), Single-machine earliness-tardiness scheduling about a common due date with tolerances, International Journal of Production Economics, 42, 217-227
  17. Yoon, S.-H. and Ventura, J.A. (2002), An application of genetic algorithms to lot-streaming flow shop scheduling, IIE Transactions, 34(9), 779-787