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Infinite split scheduling: a new lower bound of total weighted completion time on parallel machines with job release dates and unavailability periods

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  • Rabia Nessah
  • Chengbin Chu

Abstract

This paper addresses an identical parallel machine scheduling problem with job release dates and unavailability periods to minimize total weighted completion time. This problem is known to be NP-hard in the strong sense. We propose a new lower bound that can be computed in polynomial time. The test on more than 8 400 randomly generated instances shows a very significant improvement with respect to existing results for previously studied special cases: without unavailability constraints, unweighted version, or identical job release dates. For instance, the average improvement for the unweighted problem is as much as 20.43% for 2 machines, 53.03% for 7 machines and 66.70% for 15 machines. For some instances, the improvement can be even as much as 93%. Copyright Springer Science+Business Media, LLC 2010

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  • Rabia Nessah & Chengbin Chu, 2010. "Infinite split scheduling: a new lower bound of total weighted completion time on parallel machines with job release dates and unavailability periods," Annals of Operations Research, Springer, vol. 181(1), pages 359-375, December.
    • Handle: RePEc:spr:annopr:v:181:y:2010:i:1:p:359-375:10.1007/s10479-010-0752-8
    DOI: 10.1007/s10479-010-0752-8
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    Cited by:

    1. Zhe Zhang & Xiaoling Song & Huijun Huang & Yong Yin & Benjamin Lev, 2022. "Scheduling problem in seru production system considering DeJong’s learning effect and job splitting," Annals of Operations Research, Springer, vol. 312(2), pages 1119-1141, May.

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