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A note on the total completion time problem in a permutation flowshop with a learning effect

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  • Wu, Chin-Chia
  • Lee, Wen-Chiung
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    Abstract

    The concept of learning process plays a key role in production environments. However, it is relatively unexplored in the flowshop setting. In this short note, we consider a permutation flowshop scheduling problem with a learning effect where the objective is to minimize the sum of completion times or flowtime. A dominance rule and several lower bounds are established to speed up the search for the optimal solution. In addition, the performances of several well-known heuristics are evaluated when the learning effect is present.

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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 192 (2009)
    Issue (Month): 1 (January)
    Pages: 343-347

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    Handle: RePEc:eee:ejores:v:192:y:2009:i:1:p:343-347

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    Keywords: Scheduling Permutation flowshop Flowtime Learning effect;

    References

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    1. Rajendran, Chandrasekharan & Ziegler, Hans, 1997. "An efficient heuristic for scheduling in a flowshop to minimize total weighted flowtime of jobs," European Journal of Operational Research, Elsevier, vol. 103(1), pages 129-138, November.
    2. Mosheiov, Gur & Sidney, Jeffrey B., 2003. "Scheduling with general job-dependent learning curves," European Journal of Operational Research, Elsevier, vol. 147(3), pages 665-670, June.
    3. Framinan, J. M. & Leisten, R., 2003. "An efficient constructive heuristic for flowtime minimisation in permutation flow shops," Omega, Elsevier, vol. 31(4), pages 311-317, August.
    4. Chung, Chia-Shin & Flynn, James & Kirca, Omer, 2002. "A branch and bound algorithm to minimize the total flow time for m-machine permutation flowshop problems," International Journal of Production Economics, Elsevier, vol. 79(3), pages 185-196, October.
    5. Biskup, Dirk, 1999. "Single-machine scheduling with learning considerations," European Journal of Operational Research, Elsevier, vol. 115(1), pages 173-178, May.
    6. Nawaz, Muhammad & Enscore Jr, E Emory & Ham, Inyong, 1983. "A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem," Omega, Elsevier, vol. 11(1), pages 91-95.
    7. Mosheiov, Gur, 2001. "Scheduling problems with a learning effect," European Journal of Operational Research, Elsevier, vol. 132(3), pages 687-693, August.
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    Cited by:
    1. Lee, Wen-Chiung & Chung, Yu-Hsiang, 2013. "Permutation flowshop scheduling to minimize the total tardiness with learning effects," International Journal of Production Economics, Elsevier, vol. 141(1), pages 327-334.
    2. Lee, Wen-Chiung & Wu, Chin-Chia & Hsu, Peng-Hsiang, 2010. "A single-machine learning effect scheduling problem with release times," Omega, Elsevier, vol. 38(1-2), pages 3-11, February.
    3. Cheng, T.C.E. & Wu, Chin-Chia & Chen, Juei-Chao & Wu, Wen-Hsiang & Cheng, Shuenn-Ren, 2013. "Two-machine flowshop scheduling with a truncated learning function to minimize the makespan," International Journal of Production Economics, Elsevier, vol. 141(1), pages 79-86.

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