Pattern Search Algorithms for Mixed Variable Programming

dc.contributor.authorAudet, Charles
dc.contributor.authorDennis, J.E. Jr.
dc.date.accessioned2018-06-18T17:47:32Z
dc.date.available2018-06-18T17:47:32Z
dc.date.issued1999-05
dc.date.noteMay 1999 (revised February 2000)
dc.description.abstractMany engineering optimization problems involve a special kind of discrete variable that can be represented by a number, but this representation has no significance. Such variables arise when a decision involves some situation like a choice from an unordered list of categories. This has two implications: The standard approach of solving problems with continuous relaxations of discrete variables is not available, and the notion of local optimality must be defined through a user-specified set of neighboring points. We present a class of direct search algorithms to provide limit points that satisfy some appropriate necessary conditions for local optimality for such problems. We give a more expensive, version of the algorithm that guarantees additional necessary optimality conditions. A small example illustrates the differences between the two versions. A real thermal insulation system design problem illustrates the efficacy of the user controls for this class of algorithms.
dc.format.extent22 pp
dc.identifier.citationAudet, Charles and Dennis, J.E. Jr.. "Pattern Search Algorithms for Mixed Variable Programming." (1999) <a href="https://hdl.handle.net/1911/101908">https://hdl.handle.net/1911/101908</a>.
dc.identifier.digitalTR99-02
dc.identifier.urihttps://hdl.handle.net/1911/101908
dc.language.isoeng
dc.titlePattern Search Algorithms for Mixed Variable Programming
dc.typeTechnical report
dc.type.dcmiText
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
TR99-02.pdf
Size:
295.45 KB
Format:
Adobe Portable Document Format