Increasing Convex-Along-Rays Functions with Applications to Global Optimization

A. M. Rubinov and B. M. Glover
Additional contact information
A. M. Rubinov: University of Ballarat
B. M. Glover: University of Ballarat

Journal of Optimization Theory and Applications, 1999, vol. 102, issue 3, No 7, 615-642

Abstract: Abstract Increasing convex-along-rays functions are defined within an abstract convexity framework. The basic properties of these functions including support sets and subdifferentials are outlined. Applications are provided to unconstrained global optimization using the concept of excess function.

Keywords: Abstract convexity; min-type functions; convex-along-rays functions; subdifferentials; global optimum; excess function (search for similar items in EconPapers)
Date: 1999
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1023/A:1022602223919 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:joptap:v:102:y:1999:i:3:d:10.1023_a:1022602223919

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2

DOI: 10.1023/A:1022602223919

Access Statistics for this article

Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull

More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().