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Operations Research
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A Note on Heuristics of Flow-Shop Scheduling

A note on heuristics of flow-shop scheduling
descriptionPublicationkeyboard_double_arrow_right Article 01 Aug 1996Publisher:Institute for Operations Research and the Management Sciences (INFORMS)Journal:Operations Research, volume 44, pages 648-652 (issn: 0030-364X, eissn: 1526-5463, Copyright policy )
Authors: Tsung-Chyan Lai;

doi: 10.1287/opre.44.4.648

A Note on Heuristics of Flow-Shop Scheduling

Abstract

We present an O(mn) two-group (TG) heuristic for the m-machine, n-job permutation flow-shop scheduling problem. We show that heuristic TG has a worst-case performance ratio of (m + 1)/2. We also establish worst-case bounds for several heuristics proposed in the past.

Related Organizations
Keywords

Deterministic scheduling theory in operations research, \(m\)-machine, \(n\)-job permutation flow-shop scheduling, heuristic, worst-case performance ratio

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 17
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    influence
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    		 Top 10%
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Average
Top 10%
Average
bronze