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Minimizing total absolute deviation of job completion times: extensions to position-dependent processing times and parallel identical machines

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  • G Mosheiov

    (The Hebrew University)

Abstract

As a measure of variation, total absolute deviation of job completion times (TADC) has received relatively little attention in scheduling literature. Minimizing TADC on a single machine was shown to have a polynomial time solution. In this note, we extend TADC in two directions: (i) we allow position-dependent processing times and (ii) we consider parallel identical machines. We show that each of these two more general problems, and TADC with both extensions remain polynomially solvable.

Suggested Citation

  • G Mosheiov, 2008. "Minimizing total absolute deviation of job completion times: extensions to position-dependent processing times and parallel identical machines," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(10), pages 1422-1424, October.
    • Handle: RePEc:pal:jorsoc:v:59:y:2008:i:10:d:10.1057_palgrave.jors.2602480
    DOI: 10.1057/palgrave.jors.2602480
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    References listed on IDEAS

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    Cited by:

    1. Li, Gang & Wang, Xiao-Yuan & Wang, Ji-Bo & Sun, Lin-Yan, 2013. "Worst case analysis of flow shop scheduling problems with a time-dependent learning effect," International Journal of Production Economics, Elsevier, vol. 142(1), pages 98-104.
    2. Bartłomiej Przybylski, 2022. "Parallel-machine scheduling of jobs with mixed job-, machine- and position-dependent processing times," Journal of Combinatorial Optimization, Springer, vol. 44(1), pages 207-222, August.
    3. Baruch Mor & Gur Mosheiov, 2018. "A note: minimizing total absolute deviation of job completion times on unrelated machines with general position-dependent processing times and job-rejection," Annals of Operations Research, Springer, vol. 271(2), pages 1079-1085, December.
    4. Ji-Bo Wang & Ming-Zheng Wang, 2011. "Worst-case behavior of simple sequencing rules in flow shop scheduling with general position-dependent learning effects," Annals of Operations Research, Springer, vol. 191(1), pages 155-169, November.
    5. Zhang, Jun & Liu, Feng & Tang, Jiafu & Li, Yanhui, 2019. "The online integrated order picking and delivery considering Pickers’ learning effects for an O2O community supermarket," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 123(C), pages 180-199.

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