Lot-sizing with production and delivery time windows

Laurence A. Wolsey

No 2005043, LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)

Abstract: We study two different lot-sizing problems with time windows that have been proposed recently. For the case of production time windows, in which each client specific order must be produced within a given time interval, we derive tight extended formulations for both the constant capacity and uncapacitated problems with Wagner-Whitin (non-speculative) costs. For the variant with nonspecific orders, known to be equivalent to the problem in which the time windows can be ordered by time, we also show equivalence to the basic lot-sizng problem with upper bounds on the stocks. Here we derive polynomial time dynamic programming algorithms and tight extended formulations for the uncapacitated and constant capacity problems with general costs. For the problem with delivery time windows, we use a similar approach to derive tight extended formulations for both the constant capacity and uncapacitated problems with Wagner-Whitin (non-speculative) costs.

Keywords: production time windows; lot-sizing; mixed integer programming (search for similar items in EconPapers)
Date: 2005-06
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://sites.uclouvain.be/core/publications/coredp/coredp2005.html (text/html)

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:cor:louvco:2005043

Access Statistics for this paper

More papers in LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) Voie du Roman Pays 34, 1348 Louvain-la-Neuve (Belgium). Contact information at EDIRC.
Bibliographic data for series maintained by Alain GILLIS ().