Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.cor.2009.01.001
Title: Efficient heuristics for inventory placement in acyclic networks
Authors: Shu, J.
Karimi, I.A. 
Keywords: Heuristics
Inventory
Supply chain management
Issue Date: Nov-2009
Source: Shu, J., Karimi, I.A. (2009-11). Efficient heuristics for inventory placement in acyclic networks. Computers and Operations Research 36 (11) : 2899-2904. ScholarBank@NUS Repository. https://doi.org/10.1016/j.cor.2009.01.001
Abstract: The strategic safety stock placement problem is cast as a constrained separable concave minimization problem. Some network-specific algorithms do exist in the literature, but their utility is limited to small, sparse, and special supply chain network structures. In this paper, we present two efficient, easy-to-implement heuristic algorithms for placing strategic safety stock in general acyclic supply chain networks. The computational study demonstrates that the algorithms are able to obtain near-optimal (within 4% and 7% in average) solutions efficiently by solving a finite series of LPs (7%) or fixed-sized MIPs (4%). More importantly, their performance in terms of solution quality is nearly independent of the network size (for simulated instances with up to 100 stages). For general acyclic supply chain networks with 8000 nodes and 32,000 arcs, the LP-based algorithm typically finds solutions in under 5 minutes. © 2009 Elsevier Ltd. All rights reserved.
Source Title: Computers and Operations Research
URI: http://scholarbank.nus.edu.sg/handle/10635/63799
ISSN: 03050548
DOI: 10.1016/j.cor.2009.01.001
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

18
checked on Jan 17, 2018

WEB OF SCIENCETM
Citations

16
checked on Nov 21, 2017

Page view(s)

50
checked on Jan 14, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.