Scheduling jobs in a contaminated area: a model and heuristic algorithms

A Janiak () and M Y Kovalyov
Additional contact information
A Janiak: Wroclaw University of Technology
M Y Kovalyov: Belarus State University

Journal of the Operational Research Society, 2008, vol. 59, issue 7, 977-987

Abstract: Abstract Scheduling problems studied in this paper arise when some tasks have to be executed by human resources in an area contaminated with radio-active or chemical materials. The specificity of the problems is that each work period should be accompanied by a rest period whose length depends on the start time of the corresponding work period. The dependency functions are exponentially decreasing ones. The problems with a single worker and criteria of minimizing maximum lateness or total weighted completion time are proved to be NP-hard. Heuristic algorithms for their solving are developed and computational experiments are provided.

Keywords: scheduling; computational complexity; start time-dependent processing time; single machine; contaminated area (search for similar items in EconPapers)
Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://link.springer.com/10.1057/palgrave.jors.2602406 Abstract (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:59:y:2008:i:7:d:10.1057_palgrave.jors.2602406

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

DOI: 10.1057/palgrave.jors.2602406

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 ().