Shop scheduling problems with pliable jobs

S. Knust (), N. V. Shakhlevich (), S. Waldherr () and C. Weiß ()
Additional contact information
S. Knust: University of Osnabrück
N. V. Shakhlevich: University of Leeds
S. Waldherr: Technical University of Munich
C. Weiß: Fraunhofer Institute for Industrial Mathematics ITWM

Journal of Scheduling, 2019, vol. 22, issue 6, No 3, 635-661

Abstract: Abstract In this paper, we study a new type of flow shop and open shop models, which handle so-called “pliable” jobs: their total processing times are given, but individual processing times of operations which make up these jobs are flexible and need to be determined. Our analysis demonstrates that many versions of flow shop and open shop problems with pliable jobs appear to be computationally easier than their traditional counterparts, unless the jobs have job-dependent restrictions imposed on minimum and maximum operation lengths. In the latter case, most problems with pliability become NP-hard even in the case of two machines.

Keywords: Scheduling; Flow shop; Open shop; Identical parallel machines; Preemption (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s10951-019-00607-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jsched:v:22:y:2019:i:6:d:10.1007_s10951-019-00607-9

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10951

DOI: 10.1007/s10951-019-00607-9

Access Statistics for this article

Journal of Scheduling is currently edited by Edmund Burke and Michael Pinedo

More articles in Journal of Scheduling from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().