Using composite variable modeling to achieve realism and tractability in production planning: An example from automotive stamping

Ada Barlatt, Amy Cohn, Yakov Fradkin, Oleg Gusikhin and Craig Morford

IISE Transactions, 2009, vol. 41, issue 5, 421-436

Abstract: Applying traditional mathematical programming techniques to problems in production planning can lead to tremendous challenges. These include non-linearities, very large numbers of constraints and weak linear programming relaxations. To ensure tractability, problems are often either simplified in scope or limited in instance size, resulting in solutions that may no longer address important real-world issues. As an alternative, this paper considers the use of models based on composite variables (variables that capture multiple decisions simultaneously) as a way to solve complex production planning problems. The scheduling of an automotive stamping facility is used as a demonstrative example, and it is shown how composite variable models and a novel corresponding algorithm can lead to high-quality, realistic solutions with acceptable run times. In the proposed approach, batch sizes, labor availability or sequencing of part types is not restricted and the number of changeovers is not fixed a priori. In addition, sequence-dependent changeover times and varying due dates are allowed. Computational results are presented using data from Ford Motor Company.[Supplementary materials are available for this article. Go to the publisher's online edition of IIE Transactions for the following free supplemental resource: Appendix]

Date: 2009
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/07408170802512594 (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:taf:uiiexx:v:41:y:2009:i:5:p:421-436

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/uiie20

DOI: 10.1080/07408170802512594

Access Statistics for this article

IISE Transactions is currently edited by Jianjun Shi

More articles in IISE Transactions from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().