A mathematical programming approach to identification and optimization of a class of unknown systems

Charles A. Holloway

Naval Research Logistics Quarterly, 1972, vol. 19, issue 4, 663-679

Abstract: There exists a class of decision problems for which: (1) models of input‐output response functions are not available in a closed‐form, functional representation; (2) informational costs associated with learning about the response function are significant. For these problems, combining identification with optimization using mathematical programming is potentially attractive. Three approaches to the identification‐optimization problem are proposed: an outer‐linearized approximation using relaxation (OLR); an inner‐linearized approximation using restriction (ILR); and a sequential combination of inner‐ and outer‐linearized subproblems (SIO). Algorithms based on each approach are developed and computational experience reported.

Date: 1972
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/nav.3800190407

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:wly:navlog:v:19:y:1972:i:4:p:663-679

Access Statistics for this article

More articles in Naval Research Logistics Quarterly from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().