Robust solutions and risk measures for a supply chain planning problem under uncertainty

C A Poojari (), C Lucas () and G Mitra
Additional contact information
C A Poojari: Brunel University
C Lucas: Brunel University
G Mitra: Brunel University

Journal of the Operational Research Society, 2008, vol. 59, issue 1, 2-12

Abstract: Abstract We consider a strategic supply chain planning problem formulated as a two-stage stochastic integer programming (SIP) model. The strategic decisions include site locations, choices of production, packing and distribution lines, and the capacity increment or decrement policies. The SIP model provides a practical representation of real-world discrete resource allocation problems in the presence of future uncertainties which arise due to changes in the business and economic environment. Such models that consider the future scenarios (along with their respective probabilities) not only identify optimal plans for each scenario, but also determine a hedged strategy for all the scenarios. We 1) exploit the natural decomposable structure of the SIP problem through Benders’ decomposition, 2) approximate the probability distribution of the random variables using the generalized lambda distribution, and 3) through simulations, calculate the performance statistics and the risk measures for the two models, namely the expected-value and the here-and-now.

Keywords: supply chain planning; stochastic integer programming; Benders’ decomposition; generalized lambda distribution; simulation; genetic algorithm (search for similar items in EconPapers)
Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

Downloads: (external link)
http://link.springer.com/10.1057/palgrave.jors.2602381 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:1:d:10.1057_palgrave.jors.2602381

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

DOI: 10.1057/palgrave.jors.2602381

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 ().