An evolutionary approach to the design of experiments for combinatorial optimization with an application to enzyme engineering

Borrotti, Matteo (2011) An evolutionary approach to the design of experiments for combinatorial optimization with an application to enzyme engineering, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Metodologia statistica per la ricerca scientifica, 23 Ciclo. DOI 10.6092/unibo/amsdottorato/3422.
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Abstract

In a large number of problems the high dimensionality of the search space, the vast number of variables and the economical constrains limit the ability of classical techniques to reach the optimum of a function, known or unknown. In this thesis we investigate the possibility to combine approaches from advanced statistics and optimization algorithms in such a way to better explore the combinatorial search space and to increase the performance of the approaches. To this purpose we propose two methods: (i) Model Based Ant Colony Design and (ii) Naïve Bayes Ant Colony Optimization. We test the performance of the two proposed solutions on a simulation study and we apply the novel techniques on an appplication in the field of Enzyme Engineering and Design.

Abstract
Tipologia del documento
Tesi di dottorato
Autore
Borrotti, Matteo
Supervisore
Dottorato di ricerca
Scuola di dottorato
Scienze economiche e statistiche
Ciclo
23
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Evolutionary Optimization Design of Experiments Predictive Model Ant Colony Optmization Naïve Bayes Classifier Enzyme Engineering and Design
URN:NBN
DOI
10.6092/unibo/amsdottorato/3422
Data di discussione
18 Marzo 2011
URI

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