Search schemes for random optimization algorithms that preserve the asymptotic distribution
Markovian algorithms for estimating the global maximum or minimum of real valued functions defined on some domain Ω ⊂ ℝd are presented. Conditions on the search schemes that preserve the asymptotic distribution are derived. Global and local search schemes satisfying these conditions are analysed and...
| Autores: | , |
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| Tipo de documento: | artigo |
| Estado: | Versão publicada |
| Data de publicação: | 1999 |
| País: | Brasil |
| Recursos: | Universidade Estadual Paulista (UNESP) |
| Repositório: | Repositório Institucional da UNESP |
| Idioma: | inglês |
| OAI Identifier: | oai:repositorio.unesp.br:11449/228469 |
| Acesso em linha: | http://dx.doi.org/10.1239/jap/1032374637 http://hdl.handle.net/11449/228469 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Asymptotic distribution Global optimization Random search algorithms Search schemes |
| Resumo: | Markovian algorithms for estimating the global maximum or minimum of real valued functions defined on some domain Ω ⊂ ℝd are presented. Conditions on the search schemes that preserve the asymptotic distribution are derived. Global and local search schemes satisfying these conditions are analysed and shown to yield sharper confidence intervals when compared to the i.i.d. case. © 1999 Applied Probability Trust. |
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