Minimizing total completion time on a single machine with step improving jobs

Eun-Seok Kim and Daniel Oron
Additional contact information
Eun-Seok Kim: Middlesex University, London, United Kingdom
Daniel Oron: The University of Sydney Business School, Sydney, Australia

Journal of the Operational Research Society, 2015, vol. 66, issue 9, 1481-1490

Abstract: Production systems often experience a shock or a technological change, resulting in performance improvement. In such settings, job processing times become shorter if jobs start processing at, or after, a common critical date. This paper considers a single machine scheduling problem with step-improving processing times, where the effects are job-dependent. The objective is to minimize the total completion time. We show that the problem is NP-hard in general and discuss several special cases which can be solved in polynomial time. We formulate a Mixed Integer Programming model and develop an LP-based heuristic for the general problem. Finally, computational experiments show that the proposed heuristic yields very effective and efficient solutions.

Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.palgrave-journals.com/jors/journal/v66/n9/pdf/jors201491a.pdf Link to full text PDF (application/pdf)
http://www.palgrave-journals.com/jors/journal/v66/n9/full/jors201491a.html Link to full text HTML (text/html)
Access to full text is restricted to subscribers.

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:pal:jorsoc:v:66:y:2015:i:9:p:1481-1490

Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/41274

Access Statistics for this article

Journal of the Operational Research Society is currently edited by Tom Archibald and Jonathan Crook

More articles in Journal of the Operational Research Society from Palgrave Macmillan, The OR Society
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().