A new method for joint replenishment problems

R Y K Fung () and X Ma
Additional contact information
R Y K Fung: City University of Hong Kong
X Ma: An'shan Institute of Iron and Steel Technology

Journal of the Operational Research Society, 2001, vol. 52, issue 3, 358-362

Abstract: Abstract This paper considers joint replenishment problems (JRP) of n items under deterministic and constant demand. Two new algorithms for JRP are proposed, based on a pair of tighter bounds for optimal cyclic time. The proposed algorithms can be used to determine the optimal cyclic policy and the optimal strict cyclic policy. Both algorithms are qualified for JRP with small major set-up costs, while only one of them can cope with JRP with any type of major set-up costs. Numerical experiments on randomly generated problems show that the new algorithms significantly outperform the existing exact algorithms for almost all of the test problems.

Keywords: inventory; joint replenishment; deterministic demand (search for similar items in EconPapers)
Date: 2001
References: Add references at CitEc
Citations: View citations in EconPapers (19)

Downloads: (external link)
http://link.springer.com/10.1057/palgrave.jors.2601091 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:52:y:2001:i:3:d:10.1057_palgrave.jors.2601091

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

DOI: 10.1057/palgrave.jors.2601091

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 ().