An intelligent modeling system for generalized network flow problems: With application to planning for multinational firms
Richard McBride and
Daniel O'Leary
Annals of Operations Research, 1997, vol. 75, issue 0, 355-372
Abstract:
This paper presents a discussion of the Generalized Network System (GNS), a system that captures knowledge about generalized network flow problems, in order to help users formulate, solve and interpret generalized network flow problems. Although previous researchers have built intelligent systems that incorporate knowledge about linear programming, this system includes more specific knowledge about generalized network flow problems. GNS is illustrated using it in a setting that requires international financial and replan rapidly. In addition, they need to be able to model complex events and organization GNS is illustrated using it in a setting that requires international financial and replan rapidly. In addition, they need to be able to model complex events and organization structures. For example, multinational planners need to be able to plan for production in multiple countries and repatriatization of funds. GNS allows users to meet these needs. Copyright Kluwer Academic Publishers 1997
Date: 1997
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1023/A:1018975900494 (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:spr:annopr:v:75:y:1997:i:0:p:355-372:10.1023/a:1018975900494
Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479
DOI: 10.1023/A:1018975900494
Access Statistics for this article
Annals of Operations Research is currently edited by Endre Boros
More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().