A DIRECT-based approach exploiting local minimizations for the solution of large-scale global optimization problems (Articolo in rivista)

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Label
  • A DIRECT-based approach exploiting local minimizations for the solution of large-scale global optimization problems (Articolo in rivista) (literal)
Anno
  • 2010-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1007/s10589-008-9217-2 (literal)
Alternative label
  • Liuzzi, G.; Lucidi, S.; Piccialli, V. (2010)
    A DIRECT-based approach exploiting local minimizations for the solution of large-scale global optimization problems
    in Computational optimization and applications; Springer, New York (Stati Uniti d'America)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Liuzzi, G.; Lucidi, S.; Piccialli, V. (literal)
Pagina inizio
  • 353 (literal)
Pagina fine
  • 375 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.springerlink.com/content/406g25204q32lml8/ (literal)
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  • 45 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 2 (literal)
Note
  • JSTOR (literal)
  • Scopu (literal)
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Liuzzi G.: IASI, CNR Lucidi S.: Università di Roma \"La Sapienza\" Piccialli V.: Università di Roma \"Tor Vergata\" (literal)
Titolo
  • A DIRECT-based approach exploiting local minimizations for the solution of large-scale global optimization problems (literal)
Abstract
  • In this paper we propose a new algorithm for solving difficult large-scale global optimization problems. We draw our inspiration from the well-known DIRECT algorithm which, by exploiting the objective function behavior, produces a set of points that tries to cover the most interesting regions of the feasible set. Unfortunately, it is well-known that this strategy suffers when the dimension of the problem increases. As a first step we define a multi-start algorithm using DIRECT as a deterministic generator of starting points. Then, the new algorithm consists in repeatedly applying the previous multi-start algorithm on suitable modifications of the variable space that exploit the information gained during the optimization process. The efficiency of the new algorithm is pointed out by a consistent numerical experimentation involving both standard test problems and the optimization of Morse potential of molecular clusters. (literal)
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