MinFinder: Locating all the local minima of a function
| dc.contributor.author | Tsoulos, I. G. | en |
| dc.contributor.author | Lagaris, I. E. | en |
| dc.date.accessioned | 2015-11-24T17:01:26Z | |
| dc.date.available | 2015-11-24T17:01:26Z | |
| dc.identifier.issn | 0010-4655 | - |
| dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/10924 | |
| dc.rights | Default Licence | - |
| dc.subject | global optimization | en |
| dc.subject | stochastic methods | en |
| dc.subject | monte carlo | en |
| dc.subject | clustering | en |
| dc.subject | region of attraction | en |
| dc.subject | global optimization | en |
| dc.subject | algorithm | en |
| dc.title | MinFinder: Locating all the local minima of a function | en |
| heal.abstract | A new stochastic clustering algorithm is introduced that aims to locate all the local minima of a multidimensional continuous and differentiable function inside a bounded domain. The accompanying software (MinFinder) is written in ANSI C++. However, the user may code his objective function either in C++, C or Fortran 77. We compare the performance of this new method to the performance of Multistart and Topographical Multilevel Single Linkage Clustering on a set of benchmark problems. | en |
| heal.access | campus | - |
| heal.fullTextAvailability | TRUE | - |
| heal.identifier.primary | DOI 10.1016/j.cpc.2005.10.001 | - |
| heal.journalName | Computer Physics Communications | en |
| heal.journalType | peer reviewed | - |
| heal.language | en | - |
| heal.publicationDate | 2006 | - |
| heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Ηλεκτρονικών Υπολογιστών και Πληροφορικής | el |
| heal.type | journalArticle | - |
| heal.type.el | Άρθρο Περιοδικού | el |
| heal.type.en | Journal article | en |
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