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dc.contributor.author
Carnero, Mercedes del Carmen  
dc.contributor.author
Hernández, José  
dc.contributor.author
Sanchez, Mabel Cristina  
dc.contributor.author
Bandoni, Jose Alberto  
dc.date.available
2018-03-06T20:18:45Z  
dc.date.issued
2001-11  
dc.identifier.citation
Carnero, Mercedes del Carmen; Hernández, José; Sanchez, Mabel Cristina; Bandoni, Jose Alberto; An evolutionary approach for the design of nonredundant sensor networks; American Chemical Society; Industrial & Engineering Chemical Research; 40; 23; 11-2001; 5578-5584  
dc.identifier.issn
0888-5885  
dc.identifier.uri
http://hdl.handle.net/11336/38063  
dc.description.abstract
In this work, solution strategies for the optimal design of nonredundant observable linear sensor networks are discussed. The Greedy algorithm allows the problem only to be tackled for a subset of optimization criteria. Particular deterministic techniques or general evolutionary strategies are necessary to solve the problem for more complex objective functions. In this context, a procedure based on the application of genetic algorithms (GAs) and linear algebra is presented. Ad hoc operators are designed for the crossover and mutation operations because the classic genetic operators perform poorly. In contrast to ad hoc deterministic codes, which find the design solution for each specific criteria, this strategy allows the problem to be solved with different objective functions using the same implementation. Furthermore, this code is extended to handle multiobjective problems through a modification of only the selection operator. An industrial example is provided to show the efficiency of the algorithm.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
American Chemical Society  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Sensor Networks  
dc.subject
Genetic Algorithms  
dc.subject.classification
Otras Ingeniería Química  
dc.subject.classification
Ingeniería Química  
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS  
dc.title
An evolutionary approach for the design of nonredundant sensor networks  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2018-03-06T15:12:06Z  
dc.journal.volume
40  
dc.journal.number
23  
dc.journal.pagination
5578-5584  
dc.journal.pais
Estados Unidos  
dc.journal.ciudad
Washington  
dc.description.fil
Fil: Carnero, Mercedes del Carmen. Universidad Nacional de Río Cuarto. Facultad de Ingeniería; Argentina  
dc.description.fil
Fil: Hernández, José. Universidad Nacional de Río Cuarto. Facultad de Ingeniería; Argentina  
dc.description.fil
Fil: Sanchez, Mabel Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina  
dc.description.fil
Fil: Bandoni, Jose Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina  
dc.journal.title
Industrial & Engineering Chemical Research  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1021/ie000941k  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://pubs.acs.org/doi/abs/10.1021/ie000941k