GenMin: An enhanced genetic algorithm for global optimization
| dc.contributor.author | Tsoulos, I. G. | en |
| dc.contributor.author | Lagaris, I. E. | en |
| dc.date.accessioned | 2015-11-24T17:01:54Z | |
| dc.date.available | 2015-11-24T17:01:54Z | |
| dc.identifier.issn | 0010-4655 | - |
| dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/10994 | |
| dc.rights | Default Licence | - |
| dc.subject | genetic algorithm | en |
| dc.subject | genetic programming | en |
| dc.subject | grammatical evolution | en |
| dc.subject | global optimization | en |
| dc.subject | stochastic methods | en |
| dc.subject | stopping rule | en |
| dc.subject | controlled random search | en |
| dc.subject | differential evolution | en |
| dc.subject | generation | en |
| dc.title | GenMin: An enhanced genetic algorithm for global optimization | en |
| heal.abstract | A new method that employs grammatical evolution and a stopping rule for finding the global minimum of a continuous multidimensional, multimodal function is considered. The genetic algorithm used is a hybrid genetic algorithm in conjunction with a local search procedure. We list results from numerical experiments with a series of test functions and we compare with other established global optimization methods. The accompanying software accepts objective functions coded either in Fortran 77 or in C++. | en |
| heal.access | campus | - |
| heal.fullTextAvailability | TRUE | - |
| heal.identifier.primary | DOI 10.1016/j.cpc.2008.01.040 | - |
| heal.journalName | Computer Physics Communications | en |
| heal.journalType | peer reviewed | - |
| heal.language | en | - |
| heal.publicationDate | 2008 | - |
| 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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