Logo of Humboldt-Universität zu BerlinLogo of Humboldt-Universität zu Berlin
edoc-Server
Open-Access-Publikationsserver der Humboldt-Universität
de|en
Header image: facade of Humboldt-Universität zu Berlin
View Item 
  • edoc-Server Home
  • Elektronische Zeitschriften
  • Stochastic Programming E-print Series (SPEPS)
  • Volume 2005
  • View Item
  • edoc-Server Home
  • Elektronische Zeitschriften
  • Stochastic Programming E-print Series (SPEPS)
  • Volume 2005
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.
All of edoc-ServerCommunity & CollectionTitleAuthorSubjectThis CollectionTitleAuthorSubject
PublishLoginRegisterHelp
StatisticsView Usage Statistics
All of edoc-ServerCommunity & CollectionTitleAuthorSubjectThis CollectionTitleAuthorSubject
PublishLoginRegisterHelp
StatisticsView Usage Statistics
View Item 
  • edoc-Server Home
  • Elektronische Zeitschriften
  • Stochastic Programming E-print Series (SPEPS)
  • Volume 2005
  • View Item
  • edoc-Server Home
  • Elektronische Zeitschriften
  • Stochastic Programming E-print Series (SPEPS)
  • Volume 2005
  • View Item
2005-07-06Buch DOI: 10.18452/8344
The value of multi-stage stochastic programming in capacity planning under uncertainty
Huang, Kai
Ahmed, Shabbir
This paper addresses a general class of capacity planning problems under uncertainty, which arises, for example, in semiconductor tool purchase planning. Using a scenario tree to model the evolution of the uncertainties, we develop a multi-stage stochastic integer programming formulation for the problem. In contrast to earlier two-stage approaches, the multi-stage model allows for revision of the capacity expansion plan as more information regarding the uncertainties is revealed. We provide analytical bounds for the value of multi-stage stochastic programming (VMS) afforded over the two-stage approach. By exploiting a special lot-sizing substructure inherent in the problem, we develop an effient approximation scheme for the diffult multi-stage stochastic integer program and prove that the proposed scheme is asymptotically optimal. Computational experiments with realistic-scale problem instances suggest that the VMS for this class of problems is quite high. Moreover the quality and performance of the approximation scheme is very satisfactory. Fortunately, this is more so for instances for which the VMS is high.
Files in this item
Thumbnail
15.pdf — Adobe PDF — 249.3 Kb
MD5: 68b3ab4b58634afc17407b0329bd6ad5
Cite
BibTeX
EndNote
RIS
InCopyright
Details
DINI-Zertifikat 2019OpenAIRE validatedORCID Consortium
Imprint Policy Contact Data Privacy Statement
A service of University Library and Computer and Media Service
© Humboldt-Universität zu Berlin
 
DOI
10.18452/8344
Permanent URL
https://doi.org/10.18452/8344
HTML
<a href="https://doi.org/10.18452/8344">https://doi.org/10.18452/8344</a>