Semi-deterministic and genetic algorithms for global optimization of microfluidic protein folding devices

In this paper we reformulate global optimization problems in terms of boundary value problems (BVP). This allows us to introduce a new class of optimization algorithms. Indeed, current optimization methods, including non-deterministic ones, can be seen as discretizations of initial value problems fo...

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Detalles Bibliográficos
Autores: Ivorra, Benjamín Pierre Paul, Hertzog, David E., Mohammadi, Bijan, Santiago, Juan G.
Tipo de recurso: artículo
Fecha de publicación:2006
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/51336
Acceso en línea:https://hdl.handle.net/20.500.14352/51336
Access Level:acceso abierto
Palabra clave:517.938
519.8
Shape optimization
Global optimization
Dynamical systems
Boundary value problem
Microfluidic mixers.
Ecuaciones diferenciales
Investigación operativa (Matemáticas)
1202.07 Ecuaciones en Diferencias
1207 Investigación Operativa
Descripción
Sumario:In this paper we reformulate global optimization problems in terms of boundary value problems (BVP). This allows us to introduce a new class of optimization algorithms. Indeed, current optimization methods, including non-deterministic ones, can be seen as discretizations of initial value problems for differential equations, or systems of differential equations. Furthermore, in order to reduce computational time approximate state and sensitivity evaluations are introduced during optimization. Lastly, we demonstrated the efficacy of two algorithms, included in the former class, on two academic test cases and on the design of a fast microfluidic protein folding device. The aim of the latter design is to reduce mixing times of proteins to microsecond timescales. Results are compared with those obtained with a classical genetic algorithm.